Mathematics and Computer Science
La Salle University
Self-Study 2006
Mathematics and Computer Science Self-Study 2
Mathematics and Computer Science at La Salle University
Self-Study 2006
University Mission
La Salle University, dedicated in the traditions of the Christian Brothers to excellence in teaching and
to concern for both ultimate values and for the individual values of its students, is a private Roman
Catholic University committed to providing a liberal education of both general and specialized studies.
As a Catholic university, La Salle strives to offer, through effective teaching, quality education
founded on the idea that one's intellectual and spiritual development go hand in hand, complementing
and fulfilling each other. The University has, as its basic purpose, the free search for truth by teaching
its students the basic skills, knowledge, and values that they will need for a life of human dignity. The
programs of the University also aim at preparing students for informed service and progressive
leadership in their communities and to fulfilling the immediate and final goals of their lives.
Goals:
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to recruit and maintain a distinguished faculty with diverse educational and ethnic backgrounds
as guided by the principles of equal opportunity and affirmative action and sustained through
programs of development, research assistance, and retraining;
to recruit and retain qualified students, while at the same time striving to attract a more diverse
student body: socially, geographically, economically, and racially;
to maintain class sizes small enough to promote active student participation and a close
working relationship between students and faculty;
to provide quality support services that assist the learning process;
to provide learning experiences in both traditional and non-traditional settings;
to continue to foster an atmosphere supportive of interdisciplinary learning;
to provide opportunities for part-time undergraduate and graduate study, chiefly oriented
toward attainment of degrees, for students whose personal circumstances make full-time study
impossible;
to provide co-curricular opportunities which are designed to stimulate significant change and
growth in the social, emotional, spiritual and physical development of students;
to establish advisement procedures which assist students in making valid educational and career
choices;
to provide resources as appropriate for the transition to a more residential institution of regional
scope;
to sustain an atmosphere of collegiality and trust in which matters of policy and procedural
change are recognized as the mutual province of faculty, students, and administration.
As a Christian Brothers University, La Salle continues in the Catholic traditions of the innovative
educator John Baptist de La Salle, who founded the order. The University engages in programs in
which students' personal, social and religious values may take root and in which students may grow in
mature attitudes and behavior in all human relationships. The University strives to foster an
environment of faith which produces a reciprocal respect among all persons in the community and to
establish an atmosphere in which community members may openly bear witness to their convictions on
world peace and social justice.
Mathematics and Computer Science Self-Study 3
Goals:
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to continue to encourage the presence and influence of the Christian Brothers on campus;
to provide opportunities for worship and celebration and to maintain an active Campus
Ministry;
to undertake theological and religious study in a systematic and critical way and to investigate
interrelationships which emerge with other disciplines;
to maintain a fiscal policy which allows the University to attract students from modest income
levels;
to provide educational opportunities and resources for the economically and educationally
disadvantaged;
to continue to provide to the residents of the immediate La Salle neighborhood the educational
resources and expertise to improve the quality of their lives.
As a private University, La Salle strives to determine its own policies, thus providing the option of
private higher education in an area increasingly dominated by large public institutions.
Goals:
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to maintain autonomous academic admissions standards and an independent structure for
governance;
to determine our own fiscal, curricular and recruitment policies.
As an undergraduate institution, La Salle is committed to a liberal arts education which assists students
in liberating themselves from narrow interests, prejudices, and perspectives, and in learning to observe
reality with precision, to judge events and opinions critically and independently, to think logically, to
communicate effectively, and to sharpen aesthetic perception. Students are encouraged to seek
wisdom; that is, to grasp those basic principles which can give order to particular facts. The University
urges students to confront the ultimate questions of human experience: who am I? where does my
destiny lie? how am I to reach it?
Goals:
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to maintain, as the foundation of all learning, a common, comprehensive liberal arts core which
will challenge all undergraduate students with courses addressing the analytic process
(philosophical and/or scientific), the communication process (oral and written; emitted and
received), and the historical, intellectual, and creative growth of humanity;
to require students to gain thorough foundational knowledge of the subject matter of one or
more disciplines;
to expose students to an optimal mix of required and elective courses in a variety of disciplines,
providing advisement to help determine the elective choices which best serve the students'
educational needs.
Department Mission
Learning has the highest priority in the department of Mathematics and Computer Science. In La Salle
University’s Academic Bulletin, we are reminded that our goals include helping our students to observe
reality with precision, to think logically, and to communicate effectively. With the ultimate goal of
developing all of our students as self-learners, our faculty strives to research and implement teaching
strategies that effectively serve all of our students.
Mathematics and Computer Science Self-Study 4
Students should leave La Salle prepared to begin professional careers and to pursue graduate studies.
To these ends, we work to provide a classical foundation in the core of the discipline, introduce current
theories, research areas, and technologies, and demonstrate the links between theory and its
embodiment in the world of applications. Our programs do not provide a study that simply concludes
with degree completion. Rather, the programs are designed to generate the questions for continued
learning. Participants in our programs, both students and faculty, expand their thirst for learning and
develop a deeper appreciation and respect for related disciplines.
Goals:
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to remain current and to embrace the rapid changes in technology;
to provide our students with the ability to both use and develop computing technology;
to demonstrate the usefulness, pervasiveness, inherent beauty, and logical foundations of
mathematics;
to empower our students with traditional discipline studies coupled with new digital media to
expand their collegiate and professional careers;
to promote an understanding of the social and ethical implications of computing;
to work with all departments to ensure that our service courses meet the needs of their majors.
Composition of the Department
The Department of Mathematics and Computer Science consists of twenty full-time permanent and
one semi-retired one-quarter time permanent faculty. (Descriptions of the faculty’s background can be
found in the Faculty Section.) Several full-time faculty members have release time to fulfill
administrative responsibilities. A number of adjunct instructors (on average, sixteen each semester)
are used to teach our computer literacy and mathematics numeracy courses, both required by the
university core curriculum. There is one full-time undergraduate Administrative Assistant and one
full-time graduate Administrative Assistant. There is one full-time technology specialist. We
currently have 235 declared majors and 87 active graduate students. (Enrollment history can be found
in the Curriculum Section.)
Degree Offered
During the last 25 years, the department has evolved from one supporting a B. A. in Mathematics to a
department supporting six undergraduate majors and two graduate programs.
1978
1992
1993
1998
1999
2000
2001
2004
Introduction of the B.A. in Mathematics
Introduction of the B. A. in Computer Science
Introduction of the B. S. in Computer Science
Introduction of the M.A. in Computer Information Science
Introduction of the B. A. in Dart
State approval for changing the MA - CIS to MS - CIS
Introduction of the B. S. in Information Technology
Introduction of the M. S. in Information Technology Leadership
Introduction of the B. S. in Mathematics
Mathematics and Computer Science Self-Study 5
The combination of required and elective courses within each program allows the design of a course of
study based on personal interest and career objectives.
Curriculum
Our majors are a diverse group with different talents, goals, and learning styles. To better serve our
students, we have established programs that recognize these differences. Both our computer science
and mathematics programs include a B.S. for those who might pursue graduate school and a B.A. for
those planning to enter the profession upon graduation (if not before). We take care that having
separate tracks does not mean that the different curricular goals are pitted against each other. Rather,
we find it imperative that students share foundation classes during their first two years. Most entering
students are not ready to choose a track. A shared foundation enables them to make an informed
decision and it helps them to learn to respect and work with those having distinct talents and goals.
(See Appendices A and B for Curriculum Diagrams and Model Rosters.)
Because of the nature of our programs, most require several courses in related disciplines. Both
mathematics programs require courses in computing and physics. Our computer science B.A. program
includes courses in mathematics, business, and physics. Our computer science B.S. program requires
four mathematics courses as well as four physics courses. Our information technology majors are
required to complete two mathematics courses and two physics courses. Our goal is to provide as
complete an education in the area as is feasible within a four-year timeframe. Mathematics and
Physics are natural inclusions in a computing science education. Likewise, physics and computer
science are natural inclusions in a mathematics education. An additional benefit derived from these
requirements is the relative ease with which students may minor in a related discipline.
Our programs encourage students to engage in research projects (either as independent study or as joint
faculty-student projects) and to participate in internship and co-op placements. Faculty connections
with professional and public organizations and with industry help to ensure that our curricula are upto-date and consistent with professional and industry standards, and they provide additional
opportunities for student research, internships and co-op placements. These experiences enhance our
academic programs and our students’ graduate school and professional career opportunities.
The Department supports a student-centered Mathematics and Computer Science Organization.
Students are encouraged to participate in both the academic and social programs sponsored by this
club, including monthly symposia, during which students and/or faculty members present the results of
their research. Student work is typically the result of either an independent study or participation in La
Salle University’s faculty/student research program. Our students have presented at regional
conferences including Moravian College Student Mathematics Conference and Saint Joseph's
University Sigma Xi Student Research Symposium.
Program Details
In the Fall of 2002, the department revised our Computer Science B.A. curriculum. The changes were
the result of numerous conversations with local industry leaders, who expressed concern that our while
are graduates possessed excellent technology skills, their understanding of the business model was
limited, at best. The Computer Science B.A. program assures that all students completing this major
will understand the basics of the computing field (Data Communication, Database Management
Systems, and Concepts of Programming with GUIs), understand the basics of modern business
Mathematics and Computer Science Self-Study 6
practices (Business Perspectives), understand the basics of mathematics for computing (Discrete
Structures I and II), be well-versed in object-oriented design and programming techniques (Object
Programming and Introduction to Algorithms and Data Structures), and be able to demonstrate a
comprehensive knowledge of the material (Project Design and Project Implementation).
The department designed and implemented the Computer Science B.S. program in 1988. This
program is more traditional and adheres to the guidelines developed by CSAB. Computer Science B.S.
majors share many computer science courses with the B.A. majors, including the introductory courses,
advanced computer science courses, and the capstone courses (Project Design and Project
Implementation). In addition to in-depth study of computer science, B.S. majors complete four
mathematics courses and four science courses. The B.S. program is geared toward those students
intending to enroll in graduate school. Both the B.A. and the B.S. programs prepare students to make
immediate and continuous contributions to the computing field.
In the Fall of 2002, the department implemented the Information Technology major. This program is
intended for those students who are interested in the design and maintenance of computing networks
and client support systems. IT majors will graduate with an understanding of the basics of the
computing field and mathematical computing, and will have in-depth coursework in network-related
areas (LANs and Network Administration, Client-Support Systems, Applied Operating Systems,
Introduction to LINUX Administration, and Information Security). IT majors are also required to
obtain real-world experience through a three-credit internship.
The Mathematics B.A. program …
The Mathematics B.S. program …
Fulfillment of Specific goals
…
Scope and Complexity of Courses
…
Enrollment History
The information below provides a picture of enrollment trends.
Enrollment Figures
1994
1995
MTH MTH MTH CS CSC CSC
IT
IT
DArt DArt CIS ITL Total
BA
BS
ED
C
BS evening
evening
evening
BA
45
19
37
77
181
40
21
43
12
69
51
236
Mathematics and Computer Science Self-Study 7
1996
32
26
58
10
71
59
256
1997
34
23
51
12
82
115
317
1998
1999
2000
2001
2002
2003
2004
2005
39
30
33
40
40
27
19
14
22
28
26
19
8
10
6
20
55
11
27
53
50
51
47
40
44
25
54
44
17
18
16
16
64
53
39
37
24
19
16
11
110
150
116
88
82
100
63
49
355
379
465
488
471
469
372
322
12
6
6
26
30
44
42
30
37
18
16
18
22
22
19
21
76
113
126
149
118
87
69
13
16
11
11
4
3
19
28
51
34
38
Numerous national and regional studies (e.g., the National Commission on Mathematics and Science
Teaching for the 21st Century, the Council of the Great City Schools and Recruiting New Teachers,
Inc.) have documented the critical and growing shortage of mathematics teachers in middle and
secondary schools throughout the United States. The current figure for MTH/ED majors gives us
hope that things are improving at La Salle University. The number of mathematics majors remains a
concern.
As reported in Computing Research News, (Vol 17, No. 3, May, 2005), “the percentage of incoming
undergraduates indicating they would major in computer science (which includes engineering and
technical) declined by over 60% between the Fall of 2000 and 2004, and is now 70% lower than its peak in
the early 1980s.” Gina Poole (http://developers.slashdot.org/comments.pl?sid=06/05/081526255) writes
“there are a couple of reasons [for the decline in science and engineering degrees]: one is a myth, believed
by parents, students, and high school guidance counselors, that computer science and engineering jobs are
all being outsourced to China and India. This is not true. The percentage of the total number of jobs in this
space is quite small – less than 5%.”
The number of undergraduates majoring in computer-related disciplines (CSC and IT) at La Salle has
not seen a dramatic decrease since the late 80’s. We have not, however, recovered from that slump.
Data on Retention and Graduation Rates
Data compiled on undergraduates who enrolled as first or second majors in our programs from 1995 to
1999 indicate that graduation rates for those students compare favorably to the graduation rates of the
overall undergraduate population at the University.
Cohort
1995
1996
1997
1998
1999
6 –Year Graduation Rates
Size
All Majors
Percent Graduating
Percent
Who Majored in
Graduating
Computer Science,
Information
Technology or Math
741
70.4%
66.7%
648
73.6%
74.2%
834
70.7%
67.4%
663
69.5%
76.2%
802
70.3%
62.5%
Mathematics and Computer Science Self-Study 8
1995-99
Unweighted
Average
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70.9%
69.4%
Several recent graduates have enrolled in graduate school immediately after completing their
undergraduate degrees. We have alumni studying mathematics at LeHigh University, the University of
Utah, and Temple, and others studying computer science at Drexel, Temple, and Northeastern
University. On average, approximately two graduating seniors enter graduate school immediately
following their graduation from La Salle University. Anecdotal evidence suggests that several others
begin part-time graduate study within five years after earning their undergraduate degrees.
Core Courses Offered By the Department
La Salle University’s core curriculum includes five Powers courses that every student must complete,
including a Mathematics course. When the present core curriculum was implemented in 2002, we
designed a new mathematics course which would fulfill the core mathematics requirement for many
students, including Nursing and Humanities majors. MTH 150, Mathematics: Myths and Realities, is
offered every semester. This three-credit course was designed to foster an understanding of
mathematical data and their meanings. On average, we offer twelve sections of this course during the
Fall and Spring semesters. One Mathematics adjunct is responsible for teaching two sections each
semester; the other sections are taught by full-time faculty members. Business majors take MTH 114,
Applied Business Calculus, to fulfill the mathematics requirement. This four-credit course was
designed by our mathematics faculty in cooperation with members of the School of Business
Administration. One Mathematics adjunct is responsible for teaching one section during the year; the
other sections are taught by full-time faculty members. Science and Mathematics majors take MTH
120, Calculus and Analytic Geometry I, to fulfill the mathematics requirement.
The University’s core Powers core also includes an Information Technology requirement. Business,
Nursing, and Humanities majors take CSC 151, Introduction to Computing Using Packages, to fulfill
this requirement. Typically, thirty sections of this three-credit course are offered over the course of the
academic year, and most are taught by adjuncts. The department relies heavily on staff from the
Information Technology Department and the Audio-Visual Services Department to staff this course.
Science majors take CSC 152, Introduction to Computing, Mathematics and Science Applications, to
fulfill the Information Technology requirement. A waiver test is offered during the summer preceding
a student’s first year. This test is used to ascertain a student’s comfort with file management, word
processing, and spreadsheets. A score of at least 70% is needed to be waived from the Information
Technology requirement. Approximately one-fourth of the rising freshmen take the waiver exam; the
others choosing to register for the appropriate course. While the percentage of students passing the test
has increased during the last decade, it has only reached approximately 40%. Mathematics majors take
CSM 154, Mathematics Technologies, to fulfill the requirement; Computer Science and Information
Technology majors take any 200-level CSC or CSIT course.
All Powers courses supported by the department are assessed each summer. Some years, this
assessment is simply a response to the need to re-evaluate the choice of textbooks. Other years, a more
formal review is conducted.
Outcomes Assessment Review
Overall Assessment of the Program
Mathematics and Computer Science Self-Study 9
At this time, we are able to assess the effectiveness of our Computer Science programs through our
capstone courses, CSC 480, Project Design, and CSC 481, Project Implementation. These courses are
offered during the students’ senior year. There are on-going discussions about offering a modified
version of the courses during the students’ first year in order that project management skills are
introduced before actual, large-scale projects are assigned.
We use no formal methods for assessing our mathematics programs other than conversations with
those in industry who have hired our graduates. Clearly, some means need to be instituted for formal
measurement, and we have agreed that the selection of assessment strategies is a primary goal.
Informal assessment criteria certainly include both the number and quality of internship experiences
completed by our majors. Appendix C contains a list detailing experiential learning experiences.
Instruction
Instructional Modes & Formats
The primary delivery methods employed by members of the department include some combination of
lecture, discussion, group work, applied or experiential activities. The modes are appropriate to
particular courses or sets of courses. For the most part, the mode of instruction corresponds to the
level of the course. The use of lecture, directed discussion, and group work is, for the most part, used
in 200-level courses. This allows the instructor to deliver and the students to absorb a large amount of
basic information. Upper division courses for our Computer Science and Information Technology
majors benefit from more hands-on activities coupled with group work. Mathematics majors see
varying delivery methods based on the instructors comfort with the scholarship of a particular
pedagogy, and the content of the course. CSD 154, Mathematics Technologies, MTH 302,
Mathematical Foundations, and MTH 322, Differential Equations, make great use of our mathematics
lab. Most other Mathematics classes are more lecture-oriented. For all of our courses, we are
dedicated to the effective use of technology for enhancing the educational experience. The majority of
both our full-time and part-time faculty use the WebCT course management software to organize
course information and to enhance classroom instruction.
The department currently supports six computing laboratories.
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The undergraduate Math lab (Olney 125) is equipped with 24 Pentium M, 1.7 GHz notebooks.
Each notebook has 512 MB RAM, 40 GB hard drive, CD-RW/DVD drive, and a 14.1” screen.
The notebooks run Windows XP Professional and Office 2003. Maple 9.5 and MATLAB 7 are
also loaded. The lab is equipped with a SMART board, projector, and laser printer.
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The computer literacy lab (Olney 129) is equipped with 28 Pentium 4, 2.8GHz desktops. Each
machine has 512MB RAM, 40G hard drive, DVD-ROM/CD-RW drive, floppy drive, speakers,
and a 17-inch flat panel monitor. The machines run Windows XP Professional and Office 2003.
The lab is also equipped with a laser printer and a presentation system, which includes a
projector and sound system. This lab is used exclusively to support sections of the university’s
computer literacy course.
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The undergraduate CSC/graduate CIS lab (Olney 200) is equipped with 30 Pentium 4, 2.8GHz
desktops. Each machine has 512MB RAM, 40G hard drive, DVD-ROM/CD-RW drive, floppy
drive, speakers, and a 17-inch flat panel monitor. All of these machines are equipped to use
Mathematics and Computer Science Self-Study 10
removable hard drives for classes involving network applications. The machines run Windows
XP Professional and Office 2003. Microsoft Visual Studio 2005 Beta 2 and Oracle 9i are also
loaded to support the course programming requirements and database development. The lab is
equipped with a laser printer, and a presentation system, which includes a projector, DVD/VHS
player, and a sound system.
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The undergraduate Information Technology lab (Olney 201) is equipped with 25 Pentium 4,
2.80GHz desktops. Each machine has 512MB RAM, 40G hard drive, DVD-ROM/ CD-RW
drive, floppy drive, and a 17-inch flat panel monitor. The machines run Windows XP
Professional and Office 2003. Microsoft Visual Studio 2005 Beta 2 and Oracle 9i are loaded as
well. The lab is equipped with a laser printer and a presentation system, which includes a
projector and sound system.
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The undergraduate CSC/IT/DArt student lab (Olney 200A) is equipped with 9 Pentium 4,
2.80GHz desktops. Each machine has 512MB RAM, 40G hard drive, DVD-ROM/CD-RW
drive, floppy drive, speakers, and a 17-inch flat panel monitor. The machines run Windows XP
Professional and Office 2003. In addition, Microsoft Visual Studio 2005 Beta 2, Oracle 9i,
Adobe Photoshop CS2, Adobe Illustrator CS2, and Macromedia Studio MX 2004 are also
loaded. The lab is equipped with 2 scanners and a laser printer.
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The Digital Art and Multimedia Design (DArt) lab (Olney 127) is equipped with 25 Pentium 4,
2.80GHz desktops running Windows XP Professional and Office 2003. Each machine has
512MB RAM, a 40 B hard drive, DVD-ROM/CD-RW, floppy drive, speakers, and a 17-inch
flat panel monitor. Creative Audigy MP3+ sound cards are installed on 3 machines, and
Firewire cards are installed on 15 machines. The lab supports a color laser printer, a black laser
printer, 2 scanners, video capture equipment, projector, DVD/VHS player, and sound system.
The machines run multimedia packages including Adobe Photoshop CS2, Illustrator CS2,
Premiere 6.5, Macromedia Studio MX 2004, SoundForge 8, Acid Pro 5, Sonar 4 Studio
Edition, and QuarkXPress 6.5 This lab is used exclusively to support the DArt program.
Evaluation of student performance
Instructors employ a variety of methods to assess student performance. As with pedagogical methods,
some of the variation has to do with the level of the course. Traditional tools, including exams,
quizzes, and homework and programming assignments, are the most common means of evaluating
students in lower division courses. In upper division courses, particularly in Computer Science and
Information Technology, more emphasis is placed on projects. CSC 310, Computers, Ethics, and
Social Values, is a seminar for Computer Science and Information Technology majors. Assessment in
this course is based on short student presentations, a substantial paper, and presentation of this paper.
Grades are certainly the most obvious measure of a student’s learning. Based on statistics provided by
the University’s Office of Institutional Research, our department is in keeping with the grade averages
of the university. A more complete picture is obtained by looking at the various subsets of courses.
Grades assigned in our information literacy courses, CSC 151 and CSC 152, are substantially higher
than other courses offered by the department. They are, however, in line with other Powers courses.
Grades assigned in our numeracy course, MTH 150, are lower than those assigned in both other
department courses and other Powers courses. Anecdotal evidence suggests that this is simply because
MTH 150 is a mathematics course, and some in attendance (or not!) resist any efforts to make
mathematics accessible.
Mathematics and Computer Science Self-Study 11
Grades assigned in upper-division courses conform to other university department averages. Whether
it is due to an increased maturity or an expressed interest in the material, juniors and seniors tend to
obtain higher grade point averages than freshmen and sophomores.
Department Mean Grades can be found in Appendix D.
Evaluation of teaching
All instructors, from adjuncts to full professors, are required to distribute Teacher / Course Evaluation
forms at the end of each semester. The results are reviewed by the Chair of the department, and in the
case of a untenured, tenure-track faculty member, are submitted for review to the Dean (at the occasion
of one’s third-year review) and to the Promotion and Tenure Committee (at the occasion of standing
for tenure and/or applying for promotion). A copy of the evaluation form can be found in Appendix E.
The Faculty
The following tables highlight the teaching loads of our full- and part-time faculty and the courses
taught during the 2005 – 2006 academic year. A complete listing of full-time faculty teaching
assignments from Spring, 2003 through the present is presented in Appendix F.
During the Fall and Spring semesters, twenty-three adjuncts taught sections of our courses. We rely
heavily on staff from the university staff, primarily from IT and AV to teach sections of CSC 151.
This course accounted for twenty-four of the thirty-three sections in the table below, and university
staff taught fifteen of these sections.
Part-Time Faculty Teaching
Type of Course Number of Sections
Service
33
Major
2
Graduate
5
Total Enrollment
736
31
55
Average Class Size
22.3
15.5
11.0
Full-time faculty teaching assignments are summarized below. Included in the Service total are two
sections of Honors courses.
Full-Time Faculty Teaching
Type of Course Number of Sections
Service
27
Physics
8
Major
45
Graduate
12
Total Enrollment
629
127
720
133
Average Class Size
23.3
15.9
16.0
11.1
Department’s success in hiring faculty. (What factors worked for or against hiring the most qualified
applicants?)
Mathematics and Computer Science Self-Study 12
Recent hires include Dr. Anne Edlin, (Temple University), Dr. Joseph Catanio, (New Jersey Institute
of Technology), and Dr. Timothy Highley, (University of Virginia). Despite our “4 and 4” teaching
load, we have been able to attract well-qualified instructors from prestigious institutions.
Department’s record of hiring and retaining qualified women and minority faculty.
The department faculty is comprised of fourteen males and seven females. One woman is dedicated to
the DArt program, one woman is dedicated to the mathematics program, and five women are dedicated
to the graduate and undergraduate computer science and information technology programs.
Amount and Use of Non-instructional “Assigned time”
Name
Linda Elliott
Conrad Gleber
Thomas Keagy
Jon Knappenberger
Margaret McCoey
Margaret McManus
Position
Chair, Math and Computer Science
Director, DArt
Dean, Arts and Sciences
Assistant Chair, Math and Computer Science
Director, MS – CIS & MS – ITL Programs
Associate Dean, Arts and Sciences
Release Time Per Semester
Six hours
Six hours
Twelve hours
Three hours
Six hours
Twelve hours
The Chair of the department is authorized to allocate three-credit releases to two full-time faculty
members each academic year. The decision to award is based on on-going research activities and, at
times, course development. Further, full-time faculty teaching graduate courses have the option to
include the graduate course as a part of their twelve credit responsibility (thereby receiving a “graduate
increment” for the course), or may reduce their teaching load to nine credit hours (thereby foregoing
the “graduate increment”).
Several full-time faculty members serve on University committees.
Name
Stephen Andrilli
Thomas Blum
Joseph Catanio
Anne Edlin
Margaret McCoey
Gary Michalek
Michael Redmond
Committee
Concert and Lecture Committee
Resident Life Advisory
Concert and Lecture Committee
Scholarship Policy Committee
Graduate Council
Fellowship Committee
Faculty Development Committee
Full-time members of our faculty possess a wealth of expertise and are strongly committed to teaching.
Dr. Stephen Andrilli
B.A., La Salle University
M.A., Ph.D., Rutgers University
In addition to supervising our Mathematics / Education majors, Dr. Andrilli has recently taught
Business Calculus, Calculus and Analytic Geometry I, II, and III, Linear Algebra, Modern
Geometries, History of Mathematics, and Abstract Algebra.
Dr. Thomas Blum
Mathematics and Computer Science Self-Study 13
B. A., La Salle University
Ph.D., University of Rochester
Dr. Blum has recently taught Programming Concepts and GUIs, Object Programming,
Computer Architecture, Client Support Systems, Computer Electronics I and II, Web Scripting,
and General Physics I and II.
Sandra Camomile
B.F.A., University of Utah
M.F.A., Maryland Institute
Professor Camomile has recently taught Creating Multimedia, History and Theory of Digital
Art, Digital Art Studio, Color Theory, and Electronic Visual Communication.
Dr. Joseph Catanio
B.S., Rutgers University
M.S., Ph.D., New Jersey Institute of Technology
Dr. Catanio has recently taught Introduction to Information Technology, Database Management
Systems, Database Windows and Internet Applications, Project Design, and Project
Implementation.
Richard DiDio
B.A., La Salle University
Ph.D., University of Pennsylvania
Dr. DiDio has recently taught Calculus I, Differential Equations, Chaos and Fractals, and
General Physics I and II.
Dr. Anne Edlin
B. A., University of York
M.A., Ph.D., Temple University
Dr. Edlin has recently taught Business Calculus, Calculus I, II, and III, Foundations of
Mathematics, and Combinatorics.
Linda Elliott
B.A., University of Wisconsin
B.S., University of Oregon
M.A., University of Wisconsin
M.S., University of Oregon
Professor Elliott has recently taught Object Programming, Introduction to Algorithms and Data
Structures, Advanced Data Structures, Language Theory, and Operating Systems.
Dr. Conrad Gleber
B.F.A., Florida State University
M.F.A., School of the Art Institute of Chicago
Ph.D., Florida State University
Dr. Gleber has recently taught Color Theory and Digital Photography.
Dr. Timothy Highley
B.S., University of Dayton
Ph.D., University of Virginia
Dr. Highley has recently taught Programming Concepts and GUIs, Object Programming,
Introduction to Algorithms and Data Structures, and Discrete Structures I and II.
Mathematics and Computer Science Self-Study 14
Dr. Thomas Keagy
B.S., Texas Lutheran University
M.S., Ph.D., University of North Texas
Dr. Keagy has recently taught Mathematics Myths and Realities and Real Analysis.
Dr. Raymond Kirsch
B.A., La Salle University
M.S., Drexel University
Diploma, Pennsylvania Academy of Fine Arts
Ph.D., Temple University
Dr. Kirsch has recently taught Data Communication, Creating Multimedia, Animation, Game
Programming, 2D Gaming, and 3D Gaming.
Dr. Jon Knappenberger
B.A., M.A., Ph.D., Temple University
Dr. Knappenberger has recently taught Business Calculus, Calculus and Analytic Geometry I
and II, Foundations of Mathematics, Abstract Algebra, Differential Equations, Numerical
Analysis, and Number Theory.
Dr. Stephen Longo
B.A., La Salle University
M.S., LeHigh University
Ph.D., University of Notre Dame
Dr. Longo has recently taught Data Communication, LANs and Network Administration,
Introduction to LINUX Administration, and General Physics I and II.
Dr. Carl McCarty
B.A., La Salle University
M.A., Ph.D., Temple University
Dr. McCarty has recently taught Calculus and Analytic Geometry I, II, and III, Combinatorics,
Numerical Analysis, Complex Variables, and Mathematical Modeling.
Margaret McCoey
B.A., La Salle University
M.S., Villanova University
Professor McCoey has recently taught Data Communication, Database Management Systems,
Project Design, Project Implementation, and DArt Senior Project Management Seminar.
Dr. Margaret McManus
B.A., Immaculata College
M.S., Pennsylvania State University
Ph.D., Temple University
Dr. McManus has recently taught Data Communication and Database Management Systems.
Dr. Gary Michalek
B.A., Cornell University
Ph.D., Yale University
Dr. Michalek has recently taught Business Calculus, Calculus and Analytic Geometry I and II,
Abstract Algebra, Topology, and Probability and Statistics I and II.
Mathematics and Computer Science Self-Study 15
Dr. Michael Redmond
B.S., Duke University
M.S., Ph.D., Georgia Institute of Technology
Dr. Redmond has recently taught Programming Concepts and GUIs, Object Programming,
Database Management Systems, Project Design, and Project Implementation.
Dr. Jane Turk
B.A., D’Youville College
M.A., Ph.D., Temple University
Dr. Turk has recently taught Object Programming, Introduction to Algorithms and Data
Structures, Advanced Data Structures, Computers, Ethics, and Social Values, and Theory of
Algorithms.
Dr. Samuel Wiley
B.S., St. Joseph’s University
M.A., Villanova University
Ph.D., Temple University
Dr. Wiley has recently taught Database Management Systems and Database Windows and
Internet Applications.
Students
Advising
Student advising is the responsibility of all tenure-track and tenured faculty members. Faculty
advisors are assigned by the department’s Administrative Assistant with the guidance of the Chair.
Efforts are made to evenly distribute the advising responsibility across all faculty members, but the
results are often uneven. For several reasons, some instructors are saddled with more advisees than
others. The most obvious reason is the time and effort they are willing to devote to the task. Students
are required to meet with their advisor at least once each semester. Prior to pre-registration for the
following semester, faculty advisors are provided with progress reports for all of their advisees. This
form, produced by a program written by T. Blum, provides tremendous assistance to both the advisor
and advisee. With it, one can easily determine progress to date, the major courses yet to be completed,
and the university requirements yet to be completed. A sample copy of a progress report can be found
in Appendix G.
Research and Extracurricular Activities
The Department supports a student-centered Mathematics and Computer Science Organization.
Students are encouraged to participate in both the academic and social programs sponsored by this
club, including monthly symposia, during which students and/or faculty members present the results of
their research. Student work is typically the result of either an independent study or participation in La
Salle University’s faculty/student research program. This latter program, established in 2002, provides
funding for faculty and student research projects. To date, eleven of our majors have participated,
working with faculty members on topics including Cyclic words that avoid specific “bad” patterns,
Typography dating to Greek and Roman cultures through the progression to the printing press and up
to new forms of digital typography and internet fonts, as well as graffiti art dating from primitive cave
paintings to modern contemporary graffiti art, Process Development: bridging the gap between digital
Mathematics and Computer Science Self-Study 16
media art and conventional fine arts methods, 2D and 3D DirectX game programming, OpenGL and
3D game programming, Non-linear dynamics and the free-surface segregation kinetics of impurity
atoms in a metal lattice, Using Case Based Reasoning and Machine Learning to Make Accurate
Predictions, Differential equation systems modeling baseball movement, Flash, PHP, and Database
Integration, Model of Encryption Keys, and Discrete Math Graphs in Maple. Our students have
presented at regional conferences including Moravian College Student Mathematics Conference and
Saint Joseph's University Sigma Xi Student Research Symposium.
The department supports a Mathematics Tutoring Lab (Olney 124). During the typical semester, nine
junior or senior Mathematics majors staff the lab. These tutors provide aid for all mathematics courses
offered by the department, but the majority of clients are those having difficulty with MTH 150,
Mathematics: Myths and Realities or MTH 114, Applied Business Calculus.
Library
Connelly Library
The campus library encompasses 104,500 square feet on five levels and presently holds 360,000 titles
with 467,000 volumes in its collection. There are 31 public access terminals for library research. The
mathematics and computer science holdings include 491 print and on-line journals, 7,280 books, 64
videos and sound recordings, 316 examples instructional materials for mathematics-education majors,
and access to numerous databases such as the Faulkner Advisory for IT Studies, the Collection of
Computer Science Bibliographies, and IT Implications.
Department Library
The department supports a small library containing approximately 400 books and numerous journals.
A portion of the material is housed in our Mathematics Tutoring Lab (Olney 124), and the remainder is
available in one of our computing labs (Olney 200).
Departmental Governance
Policy Development
Members of the department strongly agree that shared governance is the most effective means for
decision making. We are all stakeholders. When both appropriate and feasible, all full-time and parttime members of the department are active participants in any policy development and departmental
decision. There are some obvious instances when it is not possible to consult all members of the
department. The Faculty Senate dictates that tenure deliberations be restricted to tenure-track and
tenured faculty members. A further restriction dictates that only tenured faculty may vote in such
considerations. When revisions to a specific program are under consideration, full-time members of
that program, i.e., mathematics, computer science, or Digital Arts, participate in the original
discussions. It is only after a concrete proposal has been designed that the full department is invited to
meet for a review and discussion.
Resource Allocation
Mathematics and Computer Science Self-Study 17
The department is fortunate to have five budgets at its disposal, including funds for undergraduate
mathematics and computer science, undergraduate information technology, undergraduate Digital Arts,
graduate Computer Information Science and graduate Information Technology Leadership. In addition
to expenditure categories such as duplicating, postage, lab supplies and the like, each budget contains
monies dedicated to software and hardware purchases. We are able to upgrade each of our computing
labs as well as our faculty offices on a three year cycle. All conference requests, whether to present, to
chair a panel, or simply to attend, have been supported.
Extramural Funding
Since 2000, the department has been very fortunate to receive grants approaching $1,000,000.00. The
majority of the funds have been awarded to our majors in the form of scholarship grants. Below is a
list of all State and Federal grants.
Year
2000
2001
2001
2001
2003
2006
Granting Agency
PA Link-to-Learn (CSIT Program)
PA Link-to-Learn (DArt Program)
PA Link-to-Learn (ITL Program)
National Science Foundation
National Science Foundation
National Science Foundation – Pending
Total:
Amount
$84,882.00
$117,226.00
$122,115.00
$267,460.00
$398,836.00
$364,768.00
$1,355,287.00
Type
Hardware and Software
Hardware and Software
Hardware and Software
Scholarships
Scholarships
Scholarships
Student Perceptions of the Program
For the most part, our students graduate with good feelings about their experiences with the
Mathematics and Computer Science Department. Appendix H contains preliminary results from this
year’s exit surveys.
Summation
Strengths
The faculty members are committed to maintaining currency. Our pragmatic approach to computing
ensures that both theory and application are equal parts of every major course, and both depth and
breadth are evident across our curricula. Our computing equipment and our computing labs are up-todate, due in great measure to our adequate budgets and the presence of an IT specialist. We are a
Microsoft centric department.
We are a student-centered department, always working with our students to ensure their understanding
of the material and their progress through the major, as well as working to obtain financial assistance
for our students. Faculty members demonstrate a willingness to accommodate our students, helping in
various pursuits, whether directly related to a given course or not. To better prepare our students,
Computer Science B.A., Mathematics B.A., and Information Technology majors are strongly
encouraged to pursue a minor in a related field. Every effort is made to schedule classes to support
dual majors and single or multiple minor fields of study.
Mathematics and Computer Science Self-Study 18
We are committed to maintaining manageable class sizes by capping courses at numbers that match
specific expectations and goals. For example, computer literacy courses are capped at 20 to ensure that
there is enough time to balance instruction and performance. Upper-level hands-on courses are capped
similarly to ensure that there is a balance between faculty-led instruction and student-driven group
work. Our core mathematics course and some upper-division mathematics courses can tolerate a
slightly larger class size, which is typically set at 25 students.
Weaknesses
Our student body is not a diverse group. Too often we face a computer science or information
technology class consisting solely of young white men. While this situation is certainly not unique to
La Salle University, it is nonetheless cause for grave concern. We must do more to recruit and retain
women and other minorities.
We are a Microsoft centric department.
There is some friction among department faculty members caused by perceived injustices in terms of
salary and/or teaching assignments. The problem seems to be that every faculty member feels that s/he
is doing more than any other faculty member. However, this may in fact be a symptom of life at a
small, private University in which faculty may be under-appreciated by those in administrative
positions.
Ongoing Concerns
We need to develop measures for program assessment. This may be as straightforward as designing
capstone courses for our Information Technology and Mathematics majors.
As enrollments remain stagnant, we may have reached a point where we should re-visit the number of
programs supported by our department. Can we justify three undergraduate computing programs?
Does the number of mathematics majors justify two mathematics programs? Can we continue to
support two separate graduate programs?
Are our desired learning outcomes reasonable? Are we trying to do too much or too little?
In August of 2004, the Chair and Program Directors composed and distributed a document concerning
grade inflation. The motivation was a perception that grades assigned by some instructors were
substantially higher than the department average. The document served to be the impetus for some
faculty members to re-examine their methods for determining grades. The document is enclosed in
Appendix I.
Mathematics and Computer Science Self-Study 19
Appendix A
Curriculum Diagrams (Including Pre-requisite Structures)
Course Learning Goals
Mathematics and Computer Science Self-Study 20
Computer Science - BA
Credits: 57
Courses: 18 inc. 4 electives (e)
Required Courses in Red.
MTH 160
Discrete
Structures I
PHY 201
Computer
Electronics I
CSIT 220
Data Communication
MTH 161
Discrete
Structures II
CSIT 320e
LANs and Network
Admin
CSC 321e
Client Support
Systems
CSIT Elective Block:
CSIT 322e, 37xe,
420e, 47xe
CSIT 422e
Information
Security
(pre-req: 320 or
321)
CSIT 301
(new course)
Computer
Architecture
CSC 240
Database Mgt
Systems
CSC 230
Programming
Concepts and GUIs
CSC 310e
Legal Issues
CSC 340e
Database Apps
CSC 280
Object Programming
CSC 290
Introduction to
Algorithms and
Data Structures
BUS 100 or 101
Four CSC Electives
Approved
Business Course
Approved
Business Course
CSC 480/481
Project Design
/ Project
Implementation
Mathematics and Computer Science Self-Study 21
Computer Science - BS
Credits: 70
Courses: 21 inc. 1 elective (e)
Required Courses in Red.
MTH 160
Discrete
Structures I
PHY 201
Computer
Electronics I
Physics 202
Computer
Electronics II
CSIT 220
Data Communication
MTH 161
Discrete
Structures II
CSIT 301
Computer
Architecture
CSIT 320e
LANs and Network
Admin
CSIT Elective Block:
CSIT 322e, 37xe,
420e, 47xe
CSC 321e
Client Support
Systems
CSC 240
Database Mgt
Systems
CSC 230
Programming
Concepts and GUIs
CSC 310e
Legal Issues
CSC 340e
Database Apps
CSC 280
Object Programming
CSC 290
Introduction to Algorithms
and
Data Structures
CSIT 422e
Information Security
(pre-req: 320 or
321)
Mth 120
Calc I
CSC 354
Advanced Data
Structures
Phy 105
Physics I
Phy 106
Physics II
Mth 221
Calc II
CSC 480/481
Project Design
/ Project
Implementation
CSC 366, 457, 464 and
one other approved
course
Mathematics and Computer Science Self-Study 22
CSIT 154
Introduction to
Information
Technology
(May be waived.)
Information
Technology
Credits: 53
Courses: 17 inc. 2 electives (e)
Required Courses in Red.
CSIT 220
Data Communication
CSIT 320
LANs and Network
Admin
CSIT 321
Client Support
Systems
CSC 240
Database Mgt
Systems
CSC 230
Programming
Concepts and GUIs
CSC 310
Legal Issues
(Pre-req: 220 or 240)
CSC 280
Object Programming
CSC 340e
Database Apps
(Pre-req: 220 and 240)
CSIT Elective Block:
CSIT 322e, 37xe,
421e, 47xe, and
approved CSC
courses.
CSIT 420
Applied Op Sys
MTH 160
Discrete Structures I
CSIT 422
Security
(Pre-req: 320 or 321)
PHY 201
Computer Electronics I
CSIT 460
Internship
Pre-req: permission of
Department Chair
PHY 202
Computer
Electronics II
MTH 161
Discrete Structures II
CSIT 301
Computer
Architecture
Mathematics and Computer Science Self-Study 23
Mathematics - BA
Mth 120
Calculus and
Analytic
Geometry I
CSM 154
(new course)
Mathematical
Technology
Mth 421e
Numerical
Analysis
Credits: 51
Courses: 15 including 5 electives (e)
Required Courses in Red.
Mth 221
Calculus and
Analytic
Geometry II
Mth 222
Calculus and
Analytic
Geometry III
Mth 240
Linear Algebra
Applications
Mth 410
Probability and
Statistics I
Mth 322
Differential
Equations
Mth 302
Foundations of
Mathematics
Mth 321
Real Analysis
Mth 424
Complex
Variables or
Mth 430
Topology
Phy 105
General Physics I
Mth 345e
Combinatorics
Mth 425e
Mathematical
Modeling
Mth 37x
Mth 47x
Mth 411e
Probability and
Statistics II
Mth 330e
Modern
Geometries
Mth 341
Abstract Algebra
Mth 405e
History of
Mathematics
Mathematics and Computer Science Self-Study 24
Mathematics - BS
Credits: 62
Courses: 18 including 4 electives (e)
Required Courses in Red.
Mth 120
Calculus and
Analytic
Geometry I
CSC 230
Programming
Concepts and
GUIs
Mth 421e
Numerical
Analysis
CSM 154
(new course)
Mathematical
Technology
Mth 221
Calculus and
Analytic
Geometry II
Mth 222
Calculus and
Analytic
Geometry III
Mth 240
Linear Algebra
Applications
Mth 410
Probability and
Statistics I
Mth 322
Differential
Equations
Mth 302
Foundations of
Mathematics
Mth 321
Real Analysis
Mth 424
Complex
Variables or
Mth 430
Topology
Phy 105
General Physics I
Mth 345e
Combinatorics
Mth 425e
Mathematical
Modeling
Mth 37x
Mth 47x
Mth 411e
Probability and
Statistics II
Mth 330e
Modern
Geometries
Mth 341
Abstract Algebra
Mth 405e
History of
Mathematics
Phy 106
General Physics II
Mathematics and Computer Science Self-Study 25
Learning Goals
Computer Science and Information Technology Courses
CSIT 220, Data Communication:
At the end of the course, students should be able to

Understand and be conversant in the various communication terminology and concepts.

Distinguish between the various communication technologies and their uses.
CSC 230, Programming Concepts and GUIs:
At the end of the course, students should be able

to approach problem statements with the experience and maturity necessary to produce
reasonable algorithms and then to implement correct and well-documented solutions to
these algorithms.
CSC 240, Database Management Systems:
At the end of the course, students should be able

normalize a database,

design a database based on a business problem,

generate SQL statements to update, maintain and query the database,

design a relational database using a relational software database package, and

explain transaction processing.
CSC 280, Object Programming:
At the end of the course, students should be able to

systematically carry out program development and debugging techniques.
Independently, designing, writing, testing and debugging programs,

effectively use basic programming statements including IF-THEN-ELSE, Loops,
methods,

effectively use built-in primitive data types,

effectively use classes, an implementation of the concept of abstract data types,

effectively use character and string handling, input, and output formatting,

effectively use I/O for communication with users and with files / streams,

effectively use Arrays, including arrays of objects,

understand basic searching and sorting techniques,

understand the importance of DOCUMENTED code,

design and create classes, and

analyze problems and develop algorithms for the solution.
CSC 290: Introduction to Data Structures and Algorithms:
At the end of the course, students should

Understand objects and object-oriented programming, including inheritance and
polymorphism

design and implement class hierarchies

understand and use appropriate terminology

Understand classic data structures (arrays, linked lists, stacks, queues, and binary trees),
their algorithms, and their applications

Mathematics and Computer Science Self-Study 26
Use Java classes, particularly those of the Java Collections Framework, to design
applications at a high level of abstraction

design, implement, and test solutions
CSIT 301, Computer Architecture and Hardware:
At the end of the course, students should

Understand the foundations of computer architecture and hardware components

Understand the underlying structure used to execute the actual tasks for an application

Investigate the internal processes involved in a software task and the associated
hardware components

Understand specific topics involved in computer architecture such as Instruction Sets,
Memory Architecture, Caching, Pipelining, Parallel Processing, and I/O Handling.

Understand the meaning of various hardware specifications.
CSC 310, Computers, Ethics, and Social Values:
At the end of the course, students should

understand key legal, ethical, and social issues of computing, and, as appropriate,
discuss pros and cons

be a mini-expert in two different topical areas as evidenced by presentation and paper

know sources: expert, within the literature, and electronic; and more competently
assess accuracy of information

understand the process of making an ethical decision

be motivated to continue learning in many of the topics discussed.
CSIT 320, LANs and Network Administration:
At the end of the course, students should be able to

Install server-based operating systems.

Install and maintain basic server services

Design, configure and install LANs.

Compare W2K with Win2003 and Linux
CSIT 321, Client Support Systems:
At the end of the course, students should be able to:

Understand the high-level knowledge, skills, and abilities necessary for employment in
the user support industry.

Utilize problem-solving and communication skills in addition to technical expertise to
troubleshoot common end-user support needs.

Develop their ideas and skills, both individually and in teams.

Participate effectively in a team-oriented work environment.

Setup, install, configure, and troubleshoot hardware.

Install, configure, upgrade, and maintain software.

Write and edit user documentation.

Prepare training materials and train end-users.

Administer and support computer networks.

Assess user needs and recommend computer systems.

Perform computer facilities management tasks.

Describe the components and features of a multi-level Help Desk operation.



Mathematics and Computer Science Self-Study 27
Assess Help Desk performance using metrics and reporting tools.
Apply knowledge management principles in order to maintain and query a repository of
problem resolution documentation.
Empower end-users to seek problem resolution via self-help tools and guidelines.
CSC 340, Database Windows and Internet Applications:
At the end of the course, students should be able to

Use SQL to select, modify, delete, and insert data into a database

Use Visual Basic.NET to interact with databases

Program in Visual Basic using ActiveX Data Objects (ADO.NET)

Design, develop and use components including classes and class libraries

Develop database applications using Active Server Pages (ASP.NET)

Work with XML as a transport medium
CSC 354, Data Structures:
At the end of the course, students should be able to

understand the distinguishing characteristics of each classic data structure (e.g.,
properties of a stack) in an object-oriented context

determine the appropriate data structure to use in a given situation

use class libraries for common data structures to solve problems

determine the cost (in terms of big-O notation) of an algorithm

use a recursive or an iterative approach, as appropriate.
CSC 366, Language Design and Automata Theory:
At the end of the course, students should

be able to demonstrate their understanding of the history and models of programming
languages,

understand the theory for defining languages, including finite state automata and
Backus Naur Form,

understand regular, context-free, context-sensitive, and unrestricted grammars,

understand the language translation process of compilers and interpreters, and

understand both the procedural and non-procedural programming paradigms and their
syntax, semantics, and run-time implementation.
CSC 370, Internet Programming:
At the end of the course, students should be able to

Design and program client-side web pages.

Use server-side code to dynamically construct and download client-side pages.

Configure and program sockets in order to better understand and control computernetwork communications (such as Instant Messenger) and Broadcasting Games
CSC 453, Computer Graphics:
At the end of the course, students should be able to

Create Win32 style windows

Create GDI applications

Work with DirectX 7.0 to create 2D applications

Create and use animated sprites

Understand graphics file formats including BMP, JPG


Mathematics and Computer Science Self-Study 28
Understand PC video adapter architectures and how modern computer screens are
represented by bitmaps
Understand graphics operations including line drawing, polygon fill, clipping and
compression algorithms
CSC 456, Artificial Intelligence:
At the end of the course, students should

understand the types of problems being attacked by artificial intelligence methods.

understand the methods and techniques used to attack artificial intelligence problems.

understand the various methods of representing knowledge -- logic, rules, statistical,
slot and filler

understand and be able to recreate various learning methods.

understand why Lisp has historically been used for most AI research.

be able to complete a small AI project
CSC 457, Operating Systems:
At the end of the course, students should be able to

demonstrate their understanding of the terms and concepts associated with process
management (processes, threads, CPU scheduling, synchronization, and deadlocks)

demonstrate their understanding of the terms and concepts associated with storage
management (paging, segmentation, segmentation with paging, virtual memory, filesystem interface, file-system implementation)

demonstrate their understanding of i/o systems and mass storage structure

demonstrate their understanding of distributed systems
CSC 464, Theory of Algorithms:
At the end of the course, students should be able to

apply each of the classic problem solving strategies

discuss classic applications of each strategy

determine an efficient strategy to solve a particular problem

read, trace, and understand a complex algorithm

understand the need for the complexity classes P and NP
CSC 480, Project Design:
Concepts:

The student should understand the processes involved in software engineering.

The student should understand important aspects of project management, including
tracking progress.

The student should understand the process of determining system and software
requirements.

The student should understand the importance of good design.

The student should understand design processes in Object-oriented and regular
development.

The student should understand design principles for current interface technologies.
Applications:

The student should gain experience in a significant team development project.




Mathematics and Computer Science Self-Study 29
The student should gain experience managing a significant project.
The student should gain experience carrying out interviews as part of requirements
determination.
The student should gain experience using OO design tools such as UML.
The student should gain experience doing system and interface design.
CSC 481, Project Implementation:
Concepts:

The student should understand the concepts and strategies behind system validation and
testing, and quality management.

The student should understand important aspects of change management, including
configuration management, and problem tracking.

The student should understand important aspects of project management including
managing people and estimating costs.

(time permitting) The student should understand the additional issues involved with
maintaining and evolving legacy systems.
Applications:

The student should gain further experience in a significant team development project.

The student should gain further experience managing a significant project.

The student should gain experience carrying out iterative, evolutionary prototyping.

The student should gain additional appreciation for and experience with concepts
covered in CSC 480.

The student should have a final prototype that they can be proud of.
PHY 201, Computer Electronics I:

Understand the implications of the finiteness of the representation, such as overflow and
the range of the numbers represented and its dependence on type.

Use the simulation tool to build circuits.

Understand how truth tables can be used to affect arithmetic and logical operations.

Understand basic logic gates (ANDs, ORs and NOTs) and their use in representing
arbitrary truth tables.

Simplify representations to minimize the number of logic gates (e.g. Karnaugh maps).

Understand how information is directed from location to location – addressing,
multiplexing and demultiplexing.

Understand the distinct roles of RAM and ROM.

Understand memory at the bit level (flip-flops) and word level (registers).

Modify registers to make shift registers and counters and understand their uses.

Understand the role of the bus and its implementation.

Understand the features of a simple architecture (program counter, memory address
register, accumulator, etc.)

Map out the micro-code control sequences corresponding to simple assembly-level
instructions.
PHY 202, Computer Electronics II:
At the end of the course, students should be able to



Analyze a resistor circuit and solve for unknowns.
Measure voltage, current or resistance of actual resistor circuits.
Simulate resistor circuits.

















Mathematics and Computer Science Self-Study 30
Analyze a capacitor circuit and solve for unknowns.
Collect data from actual capacitor circuits.
Simulate capacitor circuits.
Analyze an RC circuit and determine the time constant(s).
Collect data from actual RC circuits.
Simulate RC circuits.
Understand basic concepts from semiconductor theory (band, gap, doping).
Understand the role of a diode in a circuit.
Understand the characteristics of alternating current.
Understand the role of a transformer.
Understand the characteristics of a transistor.
Understand the transistor as an amplification device.
Understand the transistor as an on-off device.
Understand how transistor and diodes can be used to make logic gates.
Express and simplify a truth table.
Understand digital-to-analog conversion.
Understand various timing, smoothing and filtering circuits.
Mathematics and Computer Science Self-Study 31
Learning Goals
Mathematics Courses
MTH 120, Calculus and Analytic Geometry I:
At the end of this course, students should be able to

Demonstrate a solid understanding of the derivative and integral of a function, as well
as the fundamental applications of these concepts (e.g., calculating rates of change,
finding maximum and minimum values, calculating areas)

Understand the notions of limit and continuity

e comfortable with the basic rules involving derivatives and integrals, particularly with
regard to algebraic, exponential, logarithmic, and trigonometric functions, and be
familiar with such theorems as the Intermediate Value Theorem, the Mean Value
Theorem, and the Fundamental Theorem of Calculus.
MTH 160, Discrete Mathematics I:
At the end of the course, students should be able to

determine whether or not two statements are logically equivalent using truth tables and
various laws of logic;

work with both the existential and universal quantifiers and determine the truth value of
statements involving either or both of them;

determine whether or not a logical argument is valid using rules of inference;

work with sets and set operations;

identify functions and determine whether or not they are one-to-one or onto;

work with the basic elements of number theory and apply them to applications such as
public key cryptography;

perform basic operations with matrices (addition, multiplication, transposition)

work with sequences and series;

understand cardinality and determine whether a set is finite, countably infinite, or
uncountable;

understand and create proofs using mathematical induction;

work with recursive definitions and iteration;

and apply basic counting principles including the multiplication principle, permutations,
and combinations.
MTH 161, Discrete Mathematics II:
At the end of the course, students should be able to

apply basic probability rules and work with expected value;

understand and apply recurrence relations;

understand the differences between functions and relations;

understand the properties of relations and how they apply to equivalence relations;

understand the basics of graph theory;

apply graph theory to connectivity and Euler & Hamilton paths;

understand the difficulties encountered in shortest-path problems;

understand the basics of trees and their properties and applications;

and understand Boolean functions and their applications to logic gates and circuit
minimization.
MTH 221, Calculus and Analytic Geometry II:
Mathematics and Computer Science Self-Study 32
At the end of this course, students should have:

mastered the ability to compute various integrals and applying this knowledge to
familiar applications,

become familiar with the geometric tools of polar coordinates and conic sections (in
preparation for a three-dimensional treatment in Calculus III), and

an understanding whether certain infinite series converge or diverge, and becoming
familiar with standard tests for determining convergence/divergence (in preparation for
a more thorough treatment of series in Calculus III).
MTH 222, Calculus and Analytic Geometry III:
At the end of this course, students should have:

developed a geometric intuition by introducing vector techniques and alternate
coordinate systems to depict lines, planes, surfaces and solids in 3-space, and

applied the principles of differential and integral calculus in higher-dimensional space
(especially 3-space) to calculate tangent planes and normal vectors to surfaces, as well
as spatial areas and volumes.
MTH 240, Linear Algebra:
At the end of this course, students should have:

a solid understanding of the fundamental tools of linear algebra: vectors, matrices,
determinants, eigenvalues and eigenvalues, and how they are employed to solve
problems involving systems of linear equations.

An understanding of the abstract notions of a general vector space, linear independence
and span, basis and dimension, linear transformation, kernel and range, isomorphism,
inner product, and orthogonality. Not only are these important concepts in their own
right, but they act as a “bridge” to help prepare the student for the more abstract
treatment of mathematics in the junior/senior level mathematics courses.
MTH 302, Foundations of Mathematics:
At the end of this course, students should have:

a deeper understanding of the fundamental concepts (logic, sets, relations, functions,
etc.) that permeate the upper-level mathematics offerings, and to have the students gain
confidence in the understanding and writing of short proofs.

a full comprehension of the basic ideas on which those proofs are based.
MTH 322, Differential Equations:
At the end of the course, students should be able to:

Categorize ordinary differential equations (ODE’s) as linear vs. non-linear,
homogeneous vs. non-homogeneous, exact, etc.

Use the existence and uniqueness theorem to determine the properties of ODE
solutions.

Sketch a flow diagram/slope field of simple first order ODE's

Solve first-order linear and separable ODE's

Numerically approximate the solutions to first-order ODE's and systems of first-order
ODE’s using the simple Euler method.

Classify equilibrium points as sources, sinks, nodes, etc.

Sketch a phase portrait for a 2-dimensional system of ODE's.

Convert time-series solutions to phase space trajectories for systems of differential
equations



Mathematics and Computer Science Self-Study 33
Solve systems of linear ODE's with constant coefficients using the eigenvalue/vector
approach.
Linearize non-linear systems around equilibrium points
Use technology (calculator, Maple, Excel) to solve differential equations
MTH 330, Modern Geometries:
At the end of this course, students should have:

A more enriching immersion in Euclidean geometry than that already provided in
secondary school, calculus, and linear algebra. This includes coverage of various
collinearity and concurrency relationships (e.g., existence of the circumcenter,
orthocenter, incenter, etc. for a triangle, Menelaus’ and Ceva’s Theorems), the ninepoint circle and its properties, a categorization of all motions and similarities in the
plane and in space, and a treatment of the classical straightedge and compass
constructions of antiquity.

An introduction to The Geometer’s Sketchpad software, which allows students to
perform various constructions and facilitates their understanding of many important
theorems. This should provide a much more in-depth background for the future teacher
of Euclidean geometry on the secondary school or middle school level.

an exposure to other geometries besides the familiar Euclidean variety. Students
explore the properties of several finite geometries, as well as study the classic nonEuclidean geometries (hyperbolic and elliptic).
MTH 341, Abstract Algebra:
At the end of this course, students should have:

a deeper background in algebraic concepts and techniques, by introducing them to
various fundamental structures such as groups, rings, fields, and integral domains, their
similarities and differences, properties and substructures. In particular, many types of
groups are covered: Abelian, cyclic, permutation, dihedral, symmetric, and alternating.

an introduction to the concepts of isomorphism and homomorphism and discover how
these mappings can preserve (or fail to preserve) certain algebraic properties. Some
instructors will give less attention to groups and more attention to rings and fields, but
in either case, the basic examples of rings and fields are presented, along with many of
their elementary properties.

improved skills in the reading and writing of short mathematical proofs. Students are
expected to submit (for grading) carefully written solutions to many algebraic problems,
including a large number that involve proofs.
MTH 405, History of Mathematics:
At the end of this course, students should have:

an understanding of the major developments in mathematics over the centuries. In the
process, the student learns how the most important ideas (definitions and theorems)
arose, how these were presented and proved in the mathematical community of their
respective eras, and how they, in turn, influenced related developments in succeeding
years.

an understand how the historical culture of a particular place and time affected (and in
turn was affected by) mathematical development – that is, to give more meaning and
depth to the discipline of mathematics by placing it within its proper historical context.
MTH 410, Probability and Statistics I
Mathematics and Computer Science Self-Study 34
The main goals of the course are:

to learn what types of problems statisticans try to answer

how real-life phenomena are modelled by particular probability density

functions (pdfs)

to gain the ability to compute with random variables and find probabilities

and parameters for them

to understand how the use of statistics affects society

to prepare (along with the following course, MTH 411 – Probability and

Statistics II) for certain actuarial exams

to reinforce the techniques learned in calculus by their utilization in an

applied setting
MTH 411, Probability and Statistics II:
The main goals of the course are:

to learn what types of problems statisticians try to answer

to see how mathematical techniques can be applied to problems that involve uncertainty

to appreciate the immediacy of the field by considering several problems from current
events

to gain some appreciation of the historical development of the field

to understand what makes an estimator effective

to understand why point estimates are of no use, and why we use confidence intervals
and hypothesis tests instead

to see various techniques for addressing the same problem (e.g. t-tests, paired t-tests,
and ANOVA approaches to two-population problems)

to be introduced to the considerations involved in the design of a good statistical test

to become familiar with the available technology and its use in statistical inference

to understand the bivariate normal distribution and the formulae it suggests for
estimation (involving both the simple and the multiple linear regression models)

to see how linear algebra can be utilized in a different approach to the regression
problem, allowing the extension of the results to the multiple linear regression model

to prepare for actuarial examinations
MTH 421, Numerical Analysis:
At the end of the course, students should be able to

understand the impact of round-off error and computer arithmetic on numerical results;

approximate a function using a Taylor polynomial and calculate the bounds on its error
term;

solve one-variable equations using a variety of methods including the bisection method,
Newton’s method, and Muller’s method and estimate the error term in each case;

use a variety of methods to approximate a function by polynomials including Lagrange
Polynomials, divided differences, Hermite Polynomials, and cubic splines; know when
each of these methods is appropriate; and work with the error term in each case;

use a variety of three-point and five-point formulas to estimate the value of a derivative
at a point and estimate the resulting error;
Mathematics and Computer Science Self-Study 35

use a variety of methods to estimate the value of a definite integral including composite
trapezoidal and Simpson’s rules, Romberg integration, and Gaussian quadrature; and
work with the error term in each case;

*solve initial value problems for ordinary differential equations using Euler’s method
and Runge-Kutta methods;

*apply numerical methods to topics in linear algebra such as solving a linear system of
equations, calculating a determinant of a matrix, and determining eigenvalues and
eigenvectors;

* use a variety methods to approximate functions including approximations by least
squares, Chebyshev polynomials, rational functions, and trigonometric polynomials.

denotes optional topic
MTH 424, Complex Variables:
At the end of the course, students should be able to:

Perform arithmetic and algebra with complex numbers.

Identify Analytic Functions.

Work with complex functions including: polynomials, trigonometric functions,
exponentials and logarithms.

Evaluate Complex and Real Integrals using Cauchy’s Residue Theorems.

Understand how one subset of the complex plane can be mapped to another.
MTH 430, Topology:
At the end of the course, students should be able to:

to gain experience in expressing mathematical ideas clearly through the writing of
mathematical proofs

to understand the difficulties involved in making precise the fundamental notions in the
calculus of functions on the real line: specifically, the notions of limits and continuity of
functions

to understand the importance of compact sets with regard to continuous functions

to generalize the results on the real line to any Euclidean space

to generalize the above results to any metric space

to generalize the results to any topological space

to be able to deal with the definitions derived above in any abstract (non-mathematical
setting).

[from the instructor’s research] to understand the space of compact subsets of the
complex plane, and the behavior of a contractive function on this space (specifically the
fixed point theorem and the connections to fractals).

to appreciate that in higher mathematics the material of this course is crucial, as is the
ability to read and write mathematical proofs.

to be exposed to some of the historically important figures in the development of the
fields of topology; to see 20th and 21st century mathematics
Mathematics and Computer Science Self-Study 36
Appendix B: Model Rosters
Mathematics and Computer Science Self-Study 37
Bachelor of Science in Information Technology
FALL FRESHMAN YEAR
CSIT 154: Intro to IT
CSIT 220: Data Communication
ENG 107
Patterns of Meaning 1
Patterns of Meaning 2
FYO
16 credits
SPRING FRESHMAN YEAR
CSC 240: Database Management
CSC 230: Programming Concepts
Frameworks 1
ENG 108
COM 150
FALL SOPHOMORE YEAR
MTH 160: Discrete Structures I
CSIT 320: LANs & Nets
Patterns of Meaning 3
Patterns of Meaning 4
Frameworks 2
SPRING SOPHOMORE YEAR
CSC 280: Object Prog.
MTH 161: Discrete Structures II
Patterns of Meaning 5
Patterns of Meaning 6
Patterns of Meaning 7
16 credits
16 credits
FALL JUNIOR YEAR
CSIT 321: Client Support
PHY 201: Comp Elec. 1
CSC 310: Legal Issues
Patterns of Meaning 8
Patterns of Meaning 9
15 credits
SPRING JUNIOR YEAR
CSIT 421: App. Op. Sys.
PHY 202: Comp Elec. 2
CSIT 301: Comp. Architecture
Patterns of Meaning 10
Patterns of Meaning 11
15 credits
FALL SENIOR YEAR
CSIT 422: Security
CSIT Internship
Elective
Elective
Elective
15 credits
SPRING SENIOR YEAR
CSIT Elective
CSIT Elective
Elective
Elective
Elective
15 credits
15 credits
Mathematics and Computer Science Self-Study 38
Bachelor of Arts in Computer Science
FALL FRESHMAN YEAR
CSIT 220: Data Communication
CSC 240: Database Management
ENG 107
Patterns of Meaning 1
Patterns of Meaning 2
FYO
16 credits
SPRING FRESHMAN YEAR
CSC 230: Programming Concepts
Business Concentration 1
COM 150
ENG 108
Patterns of Meaning 3
FALL SOPHOMORE YEAR
CSC 280: Object Programming
MTH 160: Discrete Structures I
Patterns of Meaning 4
Patterns of Meaning 5
Frameworks 1
16 credits
SPRING SOPHOMORE YEAR
CSC 290: Data Structures & Algorithms
MTH 161: Discrete Structures II
Business Concentration 2
Frameworks 2
Patterns of Meaning 6
16 credits
FALL JUNIOR YEAR
PHY 201: Computer Electronics I
CSC Elective
CSC Elective
Patterns of Meaning 7
Patterns of Meaning 8
15 credits
SPRING JUNIOR YEAR
CSIT 301: Computer Architecture
Business Concentration 3
Patterns of Meaning 9
Patterns of Meaning 10
Patterns of Meaning 11
15 credits
FALL SENIOR YEAR
CSC 480: Project Design
CSC Elective
Elective
Elective
Elective
15 credits
SPRING SENIOR YEAR
CSC 481: Project Implementation
CSC Elective
Elective
Elective
Elective
15 credits
16 credits
Mathematics and Computer Science Self-Study 39
Bachelor of Science in Computer Science
FALL FRESHMAN YEAR
CSC 230: Programming. Concepts
MTH 120: Calculus I
ENG 108
Patterns of Meaning 1
Patterns of Meaning 2
FYO
17 credits
FALL SOPHOMORE YEAR
CSIT 220: Data Communication
CSC 280: Object Programming
MTH 160: Discrete Structures I
COM 150
Frameworks 1
17 credits
SPRING FRESHMAN YEAR
CSC 240: Database Management
MTH 221: Calculus II
Patterns of Meaning 3
Patterns of Meaning 4
Patterns of Meaning 5
15 credits
SPRING SOPHOMORE YEAR
CSC 290: Algorithms & Data Structures
MTH 161: Discrete Structures II
Frameworks 2
Patterns of Meaning 6
Patterns of Meaning 7
17 credits
FALL JUNIOR YEAR
PHY 201: Computer Electronics I
PHY 105: General Physics I
CSC 354: Advanced Data Str
Patterns of Meaning 8
Patterns of Meaning 9
16 credits
SPRING JUNIOR YEAR
PHY 202: Computer Electronics II
PHY 106: General Physics II
CSIT 301: Comp. Architecture
Patterns of Meaning 10
Patterns of Meaning 11
16 credits
FALL SENIOR YEAR
CSC 457: Operating Systems
CSC 480: Project Design
CSC Elective
Elective
Elective
15 credits
SPRING SENIOR YEAR
CSC 366: Language/Automata Theory
CSC 464: Theory of Algorithms
CSC 481: Project Implementation
Elective
Elective
15 credits
Mathematics and Computer Science Self-Study 40
Bachelor of Science in Mathematics
FALL FRESHMAN YEAR
MTH 120: Calculus I
ENG 107
Patterns of Meaning 1
Patterns of Meaning 2
Patterns of Meaning 3
FYO
17 credits
SPRING FRESHMAN YEAR
MTH 221: Calculus III
CSM 154: Mathematical Technology
ENG 108
Patterns of Meaning 4
Patterns of Meaning 5
FALL SOPHOMORE YEAR
MTH 222: Calculus III
MTH 240: Linear Algebra
CSC 230 or CSC 280
COM 150
15 credits
SPRING SOPHOMORE YEAR
MTH 302: Foundations of Mathematics
MTH 322: Differential Equations
Frameworks 1
Patterns of Meaning 6
Patterns of Meaning 7
16 credits
FALL JUNIOR YEAR
MTH 341: Abstract Algebra
MTH 410: Probability & Statistics I
PHY 105
Frameworks 2
Patterns of Meaning 8
16 credits
SPRING JUNIOR YEAR
MTH Elective 1
MTH Elective 2
PHY 106
Patterns of Meaning 9
Patterns of Meaning 10
16 credits
FALL SENIOR YEAR
SPRING SENIOR YEAR
MTH 424: Complex Variables or MTH 430:
Topology
MTH Elective 4
Elective
Elective
Elective
15 credits
MTH 321: Real Analysis
MTH Elective 3
Patterns of Meaning 11
Elective
Elective
15 credits
17 credits
Mathematics and Computer Science Self-Study 41
Bachelor of Arts in Mathematics
FALL FRESHMAN YEAR
MTH 120: Calculus I
ENG 107
Patterns of Meaning 1
Patterns of Meaning 2
Patterns of Meaning 3
FYO
17 credits
SPRING FRESHMAN YEAR
MTH 221: Calculus III
CSM 154: Mathematical Technology
ENG 108
COM 150
Patterns of Meaning 5
FALL SOPHOMORE YEAR
MTH 222: Calculus III
MTH 240: Linear Algebra
Frameworks 1
Patterns of Meaning 5
14 credits
SPRING SOPHOMORE YEAR
MTH 302: Foundations of Mathematics
MTH 322: Differential Equations
Frameworks 2
Patterns of Meaning 6
Patterns of Meaning 7
16 credits
FALL JUNIOR YEAR
MTH 341: Abstract Algebra
PHY 105
Patterns of Meaning 8
Patterns of Meaning 9
Elective
16 credits
SPRING JUNIOR YEAR
MTH Elective 1
MTH Elective 2
Patterns of Meaning 10
Patterns of Meaning 11
Elective
15 credits
FALL SENIOR YEAR
MTH 410: Probability & Statistics I
MTH Elective 3
Elective
Elective
Elective
15 credits
SPRING SENIOR YEAR
MTH Elective 4
MTH Elective 5
Elective
Elective
Elective
15 credits
17 credits
Mathematics and Computer Science Self-Study 42
Spring, 2006
Fall, 2005
Spring, 2005
Fall, 2004
Spring, 2004
Fall, 2003
Appendix C:
Name
Patrick Doane
Dustin Overturf
Boreseth Tum
Matthew Venanzi
Theodor Beric
Jean Castillo
Steven Humiston
Ali Hyman
Kristyn Oliveti
Peter Thompson
Peter Willis
Daniel Brooks
Michael Domzalski
Nguyen Ngo
Shi Poon
Matthew Starr
Joseph Wallace
Christopher Brower
John Bygott
Henry Heincer
Ryan Hull
Jeffrey Nagle
Ryan Tarrant
Matthew Venanzi
Matthew Donnelly
James Egan
Joseph Harrison
James Tangradi
Danielle Vermitski
Joseph Bowen
Christopher Brower
Experiential Learning
Location
The Flood Brook Union School
Fox Chase Medical Center
Mayor’s Office of Info. Services
Protivity Inc.
ASAP NetSource
Nueva Esperanza, Inc.
Federal Reserve Bank
ABO Haven, Inc.
Disney World
IDC Partners
The Vanguard Group
MidAtlantic AAA
New Jersey State Police
La Salle ResNet
V-Tech Computing
McNeil Pharmaceuticals
J&N Automobiles
North Catholic High School
Welding Pro
La Salle ResNet
Philadelphia Insurance, Inc.
Sungard Availability Services
Lockheed-Martin
JP Morgan Chase
Philadelphia Office of Comptroller
Flex Force
Mothers Home*
IBX
La Salle ResNet
DesignWrite, Inc.
North Catholic High School
Mathematics and Computer Science Self-Study 43
Spring, 2003
Fall, 2002
Spring, 2002
Fall, 2001
Spring, 2001
Lauren Devlin
Dennis Dilks
Gregory Fala
Michael Gallagher
Matthew Feehery
Joseph Harrison
Ivan Hukaluk
Matthew Isbretch
Anthony Koehl
David Luckinbill
Eric Moffet
Sopheap Prak
Richard Tedrow
Matthew Canning
Lauren Devlin
Matthew Fuhs
James Keller
William Koneski
Jessica McHale
Shi Poon
Dorian Regester
Richard Tedrow
Andrew Ballinger
Jason Burwell
Emir Dedic
Matthew Fuhs
Matthew Isbretch
Monica Konicki
James McCafferty
Jason Rivera
Dorian Regester
Jill Southron
Marc Benante
Andrew Dombroski
Vincent Luu
Laura McAlexander
Jessica McHale
Michael Mocarski
Robert Urban
Joseph Ward
Shawn Hopkins
Joseph Ward
Michael Wiacek
Michelle Yaeger
James Arleth
Kelly Ernst
Dana Gavaghan
Scott Gimpel
Northrop-Grumman
Synchronous Knowledge, Inc.
La Salle University
Estenda Solutions
IDC, Inc.
Compaction Grouting Services, Inc.
Bristol Township School District
US Dept of Justice
Atlantic Pacific Mortgage Corp.
Penn DOT
Bristol-Myers Squibb
IBX
Alloy Silberstein, CPA
County House Research, Inc.
Northop-Grumman
Fidelity Claim Services
GE Betz
Pindar Technologies
Defense Supply Center
V-Tech Computing
Lockheed Martin, Inc.
Greater Phila. Chamber of Commerce
Rosenbluth International
Saint Rose Grade School*
La Salle Connelly Library
Fidelity Claim Services
National Advocacy Center
Fox Chase Bank
Reslynx, Inc.
North Philadelphia Health System*
Lockheed Martin, Inc.
Life Insurance / Employee Benefits
ePraTech
Home Health Corp of America
US Attorney’s Office
Stephen H. Rosen & Associates
Defense Supply Center
eParTech
Motorola Corporation
GMAC Consumer Mortgage
IBX
GMAC Mortgage
US National Security Agency
Kuhn’s Florals
La Salle University ResNet
McNeil Consumer Health Care
McNeil Consumer Health Care
GMAC Consumer Mortgage
Mathematics and Computer Science Self-Study 44
Fall, 2000
Spring, 2000
Fall, 1999
* Volunteer services.
Devin Hudgens
Maureen Armstrong
Loren McClosky
Christine Benincasa
Darrel Hermasson
Vincent Luu
Michelle Palaganas
Teresa Vitelli
Thomas Zdandowski
Giuliana Ficchi
Loren McClosky
Christine Moroney
Edward O’Neill
Alisa Ryan
Institute for Civic Values
The Vanguard Group
Towers – Perrin Inc.
Philadelphia Water Department
Mayor’s Office of Community Services*
US Attorney’s Office
Towers – Perrin Inc.
Mayor’s Office of Community Services*
Merion Publications
Defense Supply Center
Towers – Perrin Inc.
Barsa Consulting LLC
McNeil Consumer Health Care
Towers – Perrin Inc.
Mathematics and Computer Science Self-Study 45
Appendix D: Departmental Mean Grades
Mathematics and Computer Science Self-Study 46
Fall, 2003
DEPARTMENT - DAY
SECTIONS
CSC - Day - Full-Time
Instructors
A
AB+
B
77
20
19
33
32.0
8.3
7.9 13.7
B17
7.1
C+
12
5.0
C
24
10.0
C9
3.7
D+
4
1.7
D
7
2.9
F
6
2.5
W
13
5.4
Sum
241
CSC - Day - Adjuncts
43
40
52
61
13.4 12.5 16.2 19.0
30
9.3
24
7.5
19
5.9
12
3.7
1
0.3
11
3.4
8
2.5
20
6.2
321
MTH - Day - Full-Time
Instructors
57
32
29
39
16.9
9.5
8.6 11.5
30
8.9
24
7.1
21
6.2
31
9.2
4
1.2
27
8.0
16
4.7
28
8.3
338
MTH - Day - Adjuncts
9
4
9
23
6.4
2.9
6.4 16.4
6
4.3
10
7.1
32
22.9
3
2.1
3
2.1
12
8.6
12
8.6
17
12.1
140
DArt - Day - Full-Time Instructors
15
13
13
11
12
16.0 13.8 13.8 11.7 12.8
6
6.4
6
6.4
3
3.2
2
2.1
7
7.4
3
3.2
3
3.2
94
UNIVERSITY PERCENTAGES - DAY SECTIONS
22.9 12.5 12.8 17.1 8.8
6.1
6.9
2.9
0.9
2.1
3.1
3.8
DEPARTMENT - EVENING
SECTIONS
CSC - Evening - Full-Time Instructors
25
3
2
6
3
5
42.4
5.1
3.4 10.2 5.1
8.5
11
18.6
0
0.0
0
0.0
0
0.0
1
1.7
3
5.1
59
CSC - Evening - Adjuncts
5
1
2
2
27.8
5.6
11.1 11.1
1
5.6
1
5.6
2
11.1
2
11.1
0
0.0
0
0.0
2
11.1
0
0.0
18
DArt - Evening - Adjuncts
16
1
2
2
55.2
3.4
6.9
6.9
1
3.4
0
0.0
3
10.3
0
0.0
0
0.0
3
10.3
0
0.0
1
3.4
29
UNIVERSITY PERCENTAGES - EVENING SECTIONS
24.6 13.8 12.3 17.4 6.2
3.9
6.0
1.6 0.5
1.9
5.4
5.5
Mathematics and Computer Science Self-Study 47
Spring, 2004
DEPARTMENT - DAY
SECTIONS
CSC - Day - Full-Time Instructors
A
AB+
B
B48
21
10
23
13
26.7 11.7
5.6
12.8 7.2
C+
13
7.2
C
15
8.3
C7
3.9
D+
5
2.8
D
7
3.9
F
4
2.2
W
14
7.8
Sum
180
CSC - Day - Adjuncts
31
50
20
57
10.6 17.1
6.8
19.5
30
10.3
17
5.8
26
8.9
34
11.6
2
0.7
6
2.1
9
3.1
10
3.4
292
MTH - Day - Full-Time
Instructors
48
22
27
40
15.5
7.1
8.7
12.9
25
8.1
21
6.8
34
11.0
16
5.2
5
1.6
24
7.7
13
4.2
35
11.3
310
MTH - Day - Adjuncts
8
3
5
13
11.9
4.5
7.5
19.4
1
1.5
10
14.9
6
9.0
1
1.5
3
4.5
4
6.0
7
10.4
6
9.0
67
DArt - Day - Full-Time Instructors
23
23
22
9
10
17.8 17.8 17.1
7.0
7.8
13
10.1
3
2.3
6
4.7
2
1.6
3
2.3
3
2.3
12
9.3
129
UNIVERSITY PERCENTAGES - DAY SECTIONS
22.9 12.5 12.8 17.1 8.8
6.1
6.9
2.9
0.9
2.1
3.1
3.8
DEPARTMENT - EVENING SECTIONS
CSC - Evening - Full-Time Instructors
28
13
2
1
0
0
60.9 28.3
4.3
2.2
0.0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2
4.3
46
CSC - Evening - Adjuncts
16
0
6
6
40.0
0.0
15.0 15.0
2
5.0
4
10.0
1
2.5
0
0.0
0
0.0
0
0.0
4
10.0
40
DArt - Evening - Full-Time Instructors
1
3
2
3
0
2
8.3
25.0 16.7 25.0 0.0 16.7
1
8.3
0
0.0
0
0.0
1
8.3
0
0.0
3
25.0
16
DArt - Evening - Adjuncts
8
0
0
1
66.7
0.0
0.0
8.3
1
8.3
0
0.0
0
0.0
0
0.0
0
0.0
2
16.7
12
UNIVERSITY PERCENTAGES - EVENING SECTIONS
24.6 13.8 12.3 17.4 6.2
3.9
6.0
1.6 0.5
1.9
5.4
5.5
1
2.5
0
0.0
0
0.0
Mathematics and Computer Science Self-Study 48
Fall, 2004
DEPARTMENT - DAY SECTIONS
CSC - Day - Full-Time Instructors
A
AB+
B
BC+
57
48
33
36
18
14
21.0 17.7 12.2 13.3
6.6
5.2
C
18
6.6
C9
3.3
D+
3
1.1
D
10
3.7
F
9
3.3
W
16
5.9
Sum
271
CSC - Day - Adjuncts
61
36
31
36
24.1 14.2 12.3 14.2
13
5.1
19
7.5
10
4.0
0
0.0
7
2.8
12
4.7
9
3.6
253
MTH - Day - Full-Time Instructors
63
22
31
51
32
28
14.8 5.2
7.3 12.0
7.5
6.6
50
11.7
35
8.2
12
2.8
31
7.3
19
4.5
52
12.2
426
MTH - Day - Adjuncts
6
5
7
33
4.9
4.1
5.7 27.0
15
12.3
20
16.4
1
0.8
10
8.2
7
5.7
10
8.2
6
4.9
122
9
7.8
9
7.8
2
1.7
0
0.0
4
3.4
1
0.9
5
4.3
116
UNIVERSITY PERCENTAGES - DAY SECTIONS
22.9 12.5 12.8 17.1
8.8
6.1
6.9
2.9
0.9
2.1
3.1
3.8
DEPARTMENT - EVENING
SECTIONS
CSC - Evening - Full-Time Instructors
9
6
2
3
2
0
25.0 16.7 5.6
8.3
5.6
0.0
3
8.3
2
5.6
4
11.1
4
11.1
0
0.0
1
2.8
36
CSC - Evening Adjuncts
6
4
2
12.8 8.5
4.3
19
7.5
2
1.6
DArt - Day - Full-Time Instructors
23
19
14
14
16
19.8 16.4 12.1 12.1 13.8
12
25.5
0
0.0
3
6.4
11
23.4
1
2.1
1
2.1
0
0.0
2
4.3
5
10.6
47
DArt - Evening - Adjuncts
3
1
1
3
17.6 5.9
5.9 17.6
2
11.8
0
0.0
2
11.8
1
5.9
1
5.9
0
0.0
1
5.9
2
11.8
17
UNIVERSITY PERCENTAGES - EVENING SECTIONS
24.6 13.8 12.3 17.4
6.2
3.9
6.0
1.6
0.5
1.9
5.4
5.5
Mathematics and Computer Science Self-Study 49
Spring, 2005
DEPARTMENT - DAY
SECTIONS
CSC - Day - Full-Time
Instructors
A
AB+
B
50
18
19
27
28.4 10.2 10.8 15.3
B9
5.1
C+
13
7.4
C
9
5.1
C5
2.8
D+
1
0.6
D
14
8.0
F
2
1.1
W
9
5.1
Sum
176
CSC - Day - Adjuncts
66
44
29
35
24.6 16.4 10.8 13.1
21
7.8
16
6.0
12
4.5
10
3.7
2
0.7
4
1.5
17
6.3
12
4.5
268
MTH - Day - Full-Time
Instructors
52
31
26
26
14.6
8.7
7.3
7.3
34
9.5
26
7.3
37
10.4
29
8.1
16
4.5
26
7.3
14
3.9
40
11.2
357
MTH - Day - Adjuncts
9
5
3
16
9.5
5.3
3.2
16.8
8
8.4
8
8.4
13
13.7
13
13.7
2
2.1
6
6.3
6
6.3
6
6.3
95
DArt - Day - Full-Time Instructors
16
28
29
23
9
11.1 19.4 20.1 16.0 6.3
6
4.2
12
8.3
8
5.6
3
2.1
2
1.4
1
0.7
7
4.9
144
UNIVERSITY PERCENTAGES - DAY
SECTIONS
20.0 12.4 12.0 16.7 8.8
6.4
7.4
3.2
1.1
2.7
3.2
4.1
Mathematics and Computer Science Self-Study 50
Fall, 2005
DEPARTMENT - DAY SECTIONS
CSC - Day - Full-Time Instructors
A
AB+
B
B59
26
34
28
5
23.5
10.4 13.5 11.2
2.0
C+
14
5.6
C
17
6.8
C17
6.8
D+
6
2.4
D
16
6.4
F
13
5.2
W
16
6.4
Sum
251
CSC - Day - Adjuncts
68
41
18
37
28.33 17.08 7.50 15.42
18
7.50
10
4.17
20
8.33
6
2.50
5
2.08
5
2.08
6
2.50
6
2.50
240
MTH - Day - Full-Time Instructors
40
24
35
46
45
10.2
6.1
8.9
11.7
11.5
30
7.6
39
9.9
28
7.1
7
1.8
37
9.4
31
7.9
31
7.9
393
MTH - Day - Adjuncts
2
1
1
15
3.7
1.9
1.9
27.8
5
9.3
5
9.3
10
18.5
4
7.4
3
5.6
2
3.7
3
5.6
3
5.6
54
DArt - Day - Full-Time Instructors
16
7
6
10
10
20.0
8.8
7.5
12.5
12.5
10
12.5
2
2.5
5
6.3
2
2.5
3
3.8
9
11.3
0
0.0
80
UNIVERSITY PERCENTAGES - DAY SECTIONS
22.7
11.7 12.5 16.5
8.4
6.0
7.4
2.7
0.9
3.0
3.9
3.9
DEPARTMENT - EVENING SECTIONS
CSC - Evening - Full-Time Instructors
A
AB+
B
BC+
6
1
2
1
3
2
27.3
4.5
9.1
4.5
13.6 9.1
C
0
0.0
C1
4.5
D+
0
0.0
D
1
4.5
F
2
9.1
W
3
13.6
Sum
22
CSC - Evening - Adjuncts
13
2
7
17
22.4
3.4
12.1 29.3
2
3.4
4
6.9
4
6.9
2
3.4
0
0.0
1
1.7
5
8.6
1
1.7
58
DArt - Evening - Adjuncts
3
1
4
4
18.8
6.3
25.0 25.0
1
6.3
1
6.3
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2
12.5
16
UNIVERSITY PERCENTAGES - EVENING SECTIONS
22.3
12.7 12.4 15.3
8.3
5.9
7.3
1.6
0.8
3.0
5.5
4.1
Mathematics and Computer Science Self-Study 51
Appendix E: Course Evaluation Form
La Salle University
Course & Faculty Evaluation Form
These forms will be reviewed by University administrators and returned to the instructor after grades have been submitted. These forms are used by faculty for course and professional
development and by the University in decisions regarding reappointment and promotion. The instructor should not be in the room when they are distributed and the instructor should not
collect the forms. Give your form to the designated proctor. If you have concerns about the way the survey was administered, please contact the instructor’s department chair or school
dean.
Course Number
INSTRUCTOR
CRN Number
SEMESTER
1. What is your class level?
FR
SO
JR
SR
Grad
Other
2. On what basis do you attend La Salle?
Full-time
Part-time
3. What is your major? _____________________________________
4. What is your expected grade for this course?
A
B
C
D
F
5. Which best describes why
you are taking this course?
Required University course
Required for major/minor
General Elective
6. In a typical week, how many hours
outside of class did you spend doing
work for this course?
Less than 1 hour
1 – 2 hours
3 – 4 hours
5 – 6 hours
7 or more hours
7. To your knowledge, was there cheating in
this course? If yes, please explain.
Yes
No
Not Sure
Mathematics and Computer Science Self-Study 53
Please indicate your level of agreement.
In this course…
Strongly Agree
Strongly Disagree
8.
hard work was required to get good grades.
5
4
3
2
1
9.
I was intellectually stimulated.
5
4
3
2
1
10. I kept up with assigned reading/course work.
5
4
3
2
1
11. I increased my knowledge of the subject.
5
4
3
2
1
Please indicate your level of agreement.
The instructor for this course…
Strongly Agree
Strongly Disagree
12. organized and planned the course effectively.
5
4
3
2
1
13. made the goals/objectives clear.
5
4
3
2
1
14. communicated course material clearly.
5
4
3
2
1
15. treated students with respect.
5
4
3
2
1
16. encouraged questions and participation.
5
4
3
2
1
17. responded effectively to student questions.
5
4
3
2
1
18. employed relevant tests and/or graded
materials.
5
4
3
2
1
19. provided helpful feedback on student work.
5
4
3
2
1
20. provided timely feedback on student work.
5
4
3
2
1
21. was available for help outside of class.
5
4
3
2
1
To provide an overall evaluation of this course, PLEASE RATE the following.
22. Rate the EFFECTIVENESS OF THE INSTRUCTOR in this course as he/she
contributed to your learning. (Try to set aside your feelings about the course itself.)
Very Effective
5
4
3
2
1
Very Ineffective
23. Rate the OVERALL VALUE OF THIS COURSE as it contributed to your
learning. (Try to set aside your feelings about the instructor.)
Very Valuable
5
4
3
2
1
Not At All Valuable
24.
Please discuss the strengths of the course.
25. Please discuss course features that could be
improved.
26.
Please discuss the strengths of the instructor.
27. Please discuss areas that the instructor could
improve.
Appendix F: Semester Credit Hours by Faculty
Mathematics and Computer Science Self-Study 56
Dr. Stephen Andrilli
Course Number
MTH 150 – 01
MTH 150 – 02
MTH 240 – 01
MTH 405 – 01
Course Name
Fall, 2003
Math: Myths and Realities
Math: Myths and Realities
Linear Algebra
History of Mathematics
Credits
SCH
3
3
3
3
78
75
54
24
231
MTH 150 – 01
MTH 150 – 02
EDC 679 – E
EDC 689 – C
Spring, 2004
Math: Myths and Realities
Math: Myths and Realities
Special Methods
Student Teaching
3
3
12
12
69
66
24
24
183
MTH 120 – 01
MTH 120 – 02
MTH 150 – 01
MTH 330 – 01
Fall, 2004
Calculus and Analytic Geometry I
Calculus and Analytic Geometry I
Math: Myths and Realities
Modern Geometries
4
4
3
3
108
104
90
33
335
MTH 114 – 03
MTH 114 – 04
EDC 470 – 56
Spring, 2005
Applied Business Calculus
Applied Business Calculus
Prac. and Prof. of Teaching
4
4
12
108
108
24
240
MTH 113 – 01
MTH 114 – 01
MTH 114 – 02
MTH 405 – 01
Fall, 2005
Algebra and Trigonometry
Applied Business Calculus
Applied Business Calculus
History of Mathematics
4
4
4
3
116
96
96
30
338
MTH 150 – 01
HON 482 – 01
EDC 475 – 21
Spring, 2006
Math: Myths and Realities
The Golden Braid
Prac. And Prof. of Teaching
3
3
3
72
21
9
102
Mathematics and Computer Science Self-Study 57
Dr. Thomas Blum
Course Number
CSC 157 – 01
CSC 362 – 01
PHY 201 – 41
Course Name
Fall, 2003
Object Programming
Data Communication
Computer Electronics I
Credits
SCH
4
3
3
56
42
69
167
CSIT 370 – 01
PHY 202 – 41
Spring, 2004
Computer Architecture
Computer Electronics II
3
3
30
42
72
CSIT 220 – 01
CSC 240 – 01
PHY 201 – 41
CIS 685 – X
Fall, 2004
Data Communication
Database Management Systems
Computer Electronics I
Independent Research
3
3
3
3
66
48
57
3
174
CSIT 301 – 01
CSD 340 – 01
CSC 4XX – 01
Spring, 2005
Computer Architecture
Web Scripting
Special Topics / Research
3
3
3
81
57
9
147
CSC 230 – A
CSIT 321 – 21
PHY 201 – 41
CIS 610 – X
Fall, 2005
Computer Concepts and GUIs
Client Support Systems
Computer Electronics I
Legal / Ethical Issues in Computing
4
3
3
3
84
54
72
6
216
CSIT 301 – 21
CSD 340 – 21
PHY 202 – 41
PHY 202 – A
Spring, 2006
Computer Architecture
Web Scripting
Computer Electronics II
Computer Electronics II
3
3
3
3
81
75
47
24
227
Mathematics and Computer Science Self-Study 58
Sandra Camomile
Course Number
ART 102 – 31
ART 220 – 01
DArt 101 – 31
DArt 101 – 01
Course Name
Fall, 2003
Digital Art Studio
Electronic Visual Communication
Intro. To Digital Art
Intro. To Digital Art
Credits
SCH
3
3
3
3
33
60
39
51
183
ART 102 – A
ART 102 – 21
ART 220 – 21
ART 374 – 41
Spring, 2004
Digital Art Studio
Digital Art Studio
Electronic Visual Communication
Digital Photography
3
3
3
3
48
69
33
51
201
ART 102 – 21
ART 102 – 31
ART 374 – 21
DArt 270 – 31
Fall, 2004
Digital Art Studio
Digital Art Studio
Digital Photography
Color Theory
3
3
3
3
48
48
51
57
204
ART 220 – A
ART 220 – 31
DArt 374 – 31
Spring, 2005
Electronic Visual Communication
Electronic Visual Communication
Digital Photography
3
3
3
39
60
69
168
ART 102 – 31
ART 215 – 01
COM 210 – 01
Fall, 2005
Digital Art Studio
Color Theory
Creating Multimedia
3
3
3
63
45
33
141
ART 220 – 31
DArt 374 – 31
DArt 374 – A
Spring, 2006
Electronic Visual Communication
Digital Photography
Digital Phogography
3
3
3
36
30
30
96
Mathematics and Computer Science Self-Study 59
Dr. Joseph Catanio
Course Number
CSC 481 – 31
CSC 481 – A
Course Name
Fall, 2004
Project Implementation
Project Implementation
Credits
SCH
3
3
21
54
75
CSC 481 – 41
CSC 481 – A
CIS 523 – A
Spring, 2005
Project Implementation
Project Implementation
Database Management
3
3
3
21
18
27
66
CSIT 154 – 31
CSIT 154 – 32
CSC 480 – 21
CIS 523 – A
Fall, 2005
Intro. To Information Technology
Intro. To Information Technology
Project Design
Database Management
3
3
3
3
66
42
39
18
165
CSC 151 – 21
CSC 151 – 23
CSC 481 – 41
INL 662 – A
Computer Literacy
Computer Literacy
Project Implementation
Mgt of IS / IT Sys. Resources
3
3
3
3
66
66
39
30
201
Mathematics and Computer Science Self-Study 60
Dr. Richard DiDio
Course Number
CSC 152-01
CSC 170-01
MTH 150-05
PHY 105-02
Course Name
Fall, 2003
Intro CSC: Science Packages
Mathematical Technology
Math: Myths & Realities
General Physics I
Credits
SCH
3
4
3
6
39
28
89
138
294
CSC 151-02
CSC 151-09
PHY 105-02
Spring, 2004
Sabbatical
Fall, 2004
Intro CSC: Packages
Intro CSC: Packages
General Physics II
3
3
6
69
66
144
279
CSM 154-01
MTH 322-01
PHY 106-02
Spring, 2005
Mathematics Technology
Differential Equations
General Physics II
4
4
6
72
44
132
248
CSC 152-01
PHY 105-02
HON 462-31
Fall, 2005
Intro CSC: Science Apps.
General Physics I
Chaos & Fractals
3
6
3
60
60
27
147
CSM 154 – 01
MTH 322 – 01
PHY 106 – 02
Spring, 2006
Mathematical Technologies
Differential Equations
General Physics II
3
3
6
48
42
54
144
Mathematics and Computer Science Self-Study 61
Dr. Anne Edlin
Course Number
MTH 120-01
MTH 150-06
MTH 150-07
MTH 221-01
Course Name
Fall, 2003
Calculus & Anal. Geom. I
Math: Myths & Realities
Math: Myths & Realities
Calculus & Anal. Geom. II
Credits
SCH
4
3
3
4
92
69
78
72
311
MTH 114-07
MTH 114-04
MTH 302-01
Spring, 2004
Applied Business Calculus
Applied Business Calculus
Foundations of Math
4
4
3
96
92
33
221
MTH 150-03
MTH 150-02
MTH 221-01
MTH 240-01
Fall, 2004
Math: Myths & Realities
Math: Myths & Realities
Calculus & Anal. Geom. II
Linear Algebra Apps.
3
3
4
4
90
78
104
88
360
MTH 150-01
MTH 150-02
MTH 302-01
Spring, 2005
Math: Myths & Realities
Math: Myths & Realities
Foundations of Math
3
3
3
75
69
63
207
MTH 150-01
MTH 150-02
MTH 240-01
MTH 345-01
Fall, 2005
Math: Myths & Realities
Math: Myths & Realities
Linear Algebra Apps.
Combinatorics
3
3
4
3
81
84
80
33
278
MTH 114 – 03
MTH 114 – 04
MTH 302 – 01
Spring, 2006
Applied Business Calculus
Applied Business Calculus
Foundations of Mathematics
4
4
3
108
108
81
297
Mathematics and Computer Science Self-Study 62
Linda Elliott
Course Number
CSC 447 A
CSC 447-21
CSC 4XX
Course Name
Fall, 2003
Applied Operating Systems
Applied Operating Systems
Internships
Credits
SCH
3
3
3
66
45
48
159
CSC 366-21
CSIT 4XX
Spring, 2004
Language Theory and Design
Internships
3
3
63
21
84
CSC 157-X
CSC 4XX
Fall, 2004
Computing & Problem Solving
Internships
4
3
4
21
25
CSC 457-21
CSIT 420-21
CSIT 4XX
Spring, 2005
Operating Systems
Applied Operating Systems
Internships/Coop
3
3
3
45
39
18
102
Fall, 2005
CSC/IT 4XX
Internships
3
24
24
CSC/IT 4XX
CSC 366 – 21
Spring, 2006
Internships
Language Theory and Design
3
3
12
42
54
Mathematics and Computer Science Self-Study 63
Dr. Timothy Highley
Course Number
CSC 230-01
MTH 160-01
Course Name
Fall, 2005
Programming Concepts & GUIs
Discrete Structures I
CSC 230 – 01
MTH 161 – 01
Spring, 2006
Programming Concepts and GUIs
Discrete Structures II
Credits
SCH
4
3
28
33
61
4
3
56
18
74
Mathematics and Computer Science Self-Study 64
Dr. Thomas Keagy
Course Number
MTH 140-21
Course Name
Spring, 2004
Discrete Math
Credits
SCH
3
45
45
MTH 321-01
Fall, 2004
Real Analysis
3
30
30
MTH 150 – 01
Fall, 2005
Math: Myths and Realities
3
87
87
Mathematics and Computer Science Self-Study 65
Dr. Raymond Kirsch
Course Number
CIS 613-A
COM 210-01
CSC 470-X
CSD 210-01
DArt 475-01
Course Name
Fall, 2003
Sabbatical
Spring, 2004
Software Engineering
Creating Multimedia
Gaming with DirectX
Creating Multimedia
Flash MX Gaming
Credits
SCH
3
3
3
3
3
21
63
6
48
48
186
CIS 607-A
COM 210-01
CSD 210-01
CSIT 220-01
Fall, 2004
Computer Graphics
Creating Multimedia
Creating Multimedia
Data Communication
3
3
3
3
18
48
66
51
183
CIS 613-BA
CIS 685-X
CSC 470-31
CSD 210-01
DArt 444-Y
DArt 475-01
Spring, 2005
Software Engineering
Independent Research
Computer Graphics
Creating Multimedia
LightWave 3D Program
Flash MX Gaming
3
3
3
3
3
3
33
3
21
48
6
30
141
CIS 613-A
CSIT 220-01
CSIT 220-02
Fall, 2005
Software Engineering
Data Communication
Data Communication
3
3
3
39
48
51
137
Dart 376 – 01
CSD 210 – 01
CIS 678 – A
Spring, 2006
Animation
Creating Multimedia
Gaming for Advertising
3
3
3
51
66
24
141
Mathematics and Computer Science Self-Study 66
Dr. Jon Knappenberger
Course Number
MTH 150-03
MTH 150-04
MTH 150-08
MTH 410-01
MTH 4XX
Course Name
Fall, 2003
Math: Myths & Realities
Math: Myths & Realities
Math: Myths & Realities
Prob. and Stat. I
Num. Methods / Number Theory
Credits
SCH
3
3
3
3
3
78
33
60
57
3
231
MTH 114-08
MTH 114-06
MTH 140-A
MTH 322-01
Spring, 2004
Applied Business Calculus
Applied Business Calculus
Discrete Math
Differential Equations
4
4
3
3
88
88
33
45
254
MTH 114-02
MTH 114-01
MTH 160-01
Fall, 2004
Applied Business Calculus
Applied Business Calculus
Discrete Structures
4
4
3
120
120
69
309
MTH 114-05
MTH 114-07
MTH 160-01
Spring, 2005
Applied Business Calculus
Applied Business Calculus
Discrete Structures II
4
4
3
112
104
33
249
MTH 114-03
MTH 114-04
CSC 151-31
Fall, 2005
Applied Business Calculus
Applied Business Calculus
Intro. CSC: Packages
4
4
3
100
88
69
257
MTH 114 – 05
MTH 114 – 06
Spring, 2006
Applied Business Calculus
Applied Business Calculus
4
4
108
108
216
Mathematics and Computer Science Self-Study 67
Dr. Stephen Longo
Course Number
CIS 625-BA
CSC 362-01
CSC 373-31
PHY 105-01
Course Name
Fall, 2003
Internet Programming
Network & Coop Process
Object Programming-Java
General Physics I
Credits
SCH
3
3
3
6
48
63
42
126
279
CSC 362-01
CSIT 371-31
INL 644-BA
INL 880-A
PHY 106-01
Spring, 2004
Network & Coop Process
Information Security
Data Security Technologies
Integrative Capstone
General Physics II
3
3
3
3
6
72
51
54
6
150
333
CIS 540-A
CSIT 320-31
PHY 105-01
Fall, 2004
Data Com: Internetworking
LANs & Network Admin.
General Physics I
3
3
6
30
48
132
210
CSIT 422-41
INL 644-A
PHY 106-01
Spring, 2005
Introduction to Linux
Data Securities Technologies
General Physics II
3
3
6
60
45
150
260
PHY 105-01
CSIT 320-41
CIS 625-BA
Fall, 2005
General Physics I
LANs and Network Admin.
Internet Programming
6
3
3
138
54
36
228
PHY 106 – 01
PHY 106 – 21
CSIT 370 – A
INL 644 – A
Spring, 2006
General Physics II
General Physics II
Routers and Switchers
Data Security Technologies
6
6
3
3
120
84
57
33
294
Mathematics and Computer Science Self-Study 68
Dr. Carl McCarty
Course Number
MTH 120-02
MTH 120-03
MTH 221-01
MTH 345-01
Course Name
Fall, 2003
Calculus & Anal. Geom. I
Calculus & Anal. Geom. I
Calculus & Anal. Geom. II
Combinatorics
Credits
SCH
4
4
4
3
64
80
52
24
220
MTH 120-01
MTH 221-01
MTH 424-01
MTH 444-X
Spring, 2004
Calculus & Anal. Geom. I
Calculus & Anal. Geom. II
Complex Variables
Advanced Combinatorics Maple
4
4
3
3
112
112
21
3
248
MTH 120-03
MTH 221-01
MTH 425-01
Fall, 2004
Calculus & Anal. Geom. I
Calculus & Anal. Geom. II
Math Modeling
4
4
3
76
36
18
130
MTH 120-01
MTH 221-01
MTH 421-01
MTH 444-X
Spring, 2005
Calculus & Anal. Geom. I
Calculus & Anal. Geom. II
Numerical Analysis
Graphical Prob. Slvd. In Maple
4
4
3
3
140
88
30
3
261
MTH 120-01
MTH 221-01
MTH 222-01
Fall, 2005
Calculus & Anal. Geom. I
Calculus & Anal. Geom. II
Calculus & Anal. Geom. II
4
4
4
92
20
88
200
MTH 120 – 01
MTH 221 – 01
MTH 424 – 01
Spring, 2006
Calculus and Analytic Geometry I
Calculus and Analytic Geometry II
Complex Variables
4
4
3
124
104
51
279
Mathematics and Computer Science Self-Study 69
Margaret McCoey
Course Number
COM 210-01
DArt 430-21
DArt 461-51
INL 642-A
Course Name
Fall, 2003
Creating Multimedia
Advanced Authoring
DArt Internship
Data Communication Tech
Credits
SCH
3
3
3
3
60
72
30
27
189
CSD 340-21
DArt 4XX
DArt 480-21
INL 664-BA
Spring, 2004
Web Scripting
DArt Internship
DArt Seminar
Tech Mgt. & Govt. Regulations
3
3
3
3
69
18
63
21
171
CIS 656-BA
CSC 151-06
CSC 240-01
DArt 430-01
DArt 461-51
DArt 481-51
Fall, 2004
E-Com: Comp Advantage
Intro CSC: Packages
Database Mgt. Systems
Advanced Authoring
Internship
Senior Portfolio
3
3
3
3
3
3
42
69
30
51
12
6
210
CIS/D 4XX
DArt 480-01
INL 631-BA
INL 880-X
CIS 681-X
Spring, 2005
PD&I/Internship/Capstone
DArt Seminar
Technology Architectures
Integrative Capstone
Project Design & Implementation
3
3
3
3
3
12
69
33
12
3
129
INL 664-BA
CIS 681-Y
Fall, 2005
Technology Mgt & Gov Regulations
Project Design & Implementation I
3
3
30
3
33
Dart 480 – 01
CIS 679 – A
Spring, 2006
Dart Seminar
Middleware Architecture
3
3
60
36
96
Mathematics and Computer Science Self-Study 70
Dr. Margaret McManus
Course Number
CIS 523-A
Course Name
Spring, 2004
Data Proc & Database Mgt
Credits
SCH
3
27
27
CSC 240-21
Spring, 2005
Database Mgt Systems
3
69
69
CSC 240 – A
Spring, 2006
Database Management Systems
3
45
45
Mathematics and Computer Science Self-Study 71
Dr. Gary Michalek
Course Number
MTH 114-01
MTH 114-02
MTH 411-01
Course Name
Fall, 2003
Sabbatical
Spring, 2004
Applied Business Calculus
Applied Business Calculus
Probability & Stat. II
Credits
SCH
4
4
3
88
92
45
225
MTH 113-01
MTH 150-05
MTH 150-04
MTH 341-01
Fall, 2004
Algebra and Trig.
Math: Myths & Realities
Math: Myths & Realities
Abstract Algebra
4
4
4
3
84
108
120
57
369
MTH 114-02
MTH 114-01
MTH 430-01
Spring, 2005
Applied Business Calculus
Applied Business Calculus
Topology
4
4
3
108
104
33
245
MTH 101-01
MTH 120-02
MTH 120-03
MTH 410-01
Fall, 2005
Intermediate Algebra
Calculus & Analytic Geometry I
Calculus & Analytic Geometry I
Probability & Stat. I
3
4
4
3
69
68
92
60
289
MTH 114 – 01
MTH 114 – 02
MTH 411 – 01
Spring, 2006
Applied Business Calculus
Applied Business Calculus
Probability and Statistics II
4
4
3
108
100
36
244
Mathematics and Computer Science Self-Study 72
Dr. Michael Redmond
Course Number
CIS 624-A
CSC 152-02
CSC 264-02
CSC 480-21
Course Name
Fall, 2003
Data Warehouses
Intro. CSC: Science Pkgs.
Data Base Mgt. Systems
Project Design
Credits
SCH
3
3
3
3
36
60
39
66
201
CIS 636-A
CSC 470-41
CSC 481-31
Spring, 2004
Adv. Computing with Java
Data Warehousing
Project Implementation
3
3
3
24
42
45
111
CIS 624 BA
CSC 151-22
CSC 230-21
Fall, 2004
Data Warehouses
Intro CSC: Packages
Programming Concepts & GUIs
3
3
4
60
69
56
185
CIS 636-BA
CSC 230-01
CSC 444-X
Spring, 2005
Adv. Computing with Java
Programming Concepts & GUIs
Data Mining Research
3
5
3
24
72
3
99
CIS 624-A
CSC 470-X
CSC 470-A
CSC 240-21
Fall, 2005
Data Warehouses
3D Multi-Player Gaming
Data Mining
Database Management Systems
3
3
3
3
42
3
54
63
162
CSC 152 – 01
CSC 240 – 01
CIS 636 – A
Spring, 2006
Intro. To Computing for Sciences
Database Management Systems
Adv. Computing With Java
3
3
3
42
48
27
117
Mathematics and Computer Science Self-Study 73
Dr. Jane Turk
Course Number
CIS 630-A
CIS 685-X
CSC 151-C
CSC 354-01
Course Name
Fall, 2003
Component Programming
Independent Research
Intro. CSC Packages
Data Structures
Credits
SCH
3
3
3
3
57
3
45
33
138
CIS 630-BA
CSC 177-31
CSC 352-41
INL 880-B
INL 880-A
Spring, 2004
Component Programming
Programming with Java
Computers & Ethics
Integrative Capstone
Integrative Capstone
3
4
3
3
3
33
32
66
9
6
146
CIS 630-BA
CSC 310-A
CSC 310-41
CSC 354-31
Fall, 2004
Component Programming
Computers & Ethics
Computers & Ethics
Data Structures
3
3
3
3
42
21
33
48
144
CIS 630-A
CSC 280-21
CSC 464-21
INL 880-W
Spring, 2005
Component Programming
Object Programming
Theory of Algorithms
Integrative Capstone
3
4
3
3
21
60
42
6
129
CSC 290-21
CSC 280-21
CIS 630-BA
Fall, 2005
Intro. Data Structure/Algorithms
Object Programming
Component Programming
4
4
3
68
40
30
138
CSC 280 – 01
CSC 290 – 01
CSC 310 – 41
CIS 610 – A
Spring, 2006
Object Programming
Algorithms and Data Structures
Computers and Ethics
Computers and Ethics
4
4
3
3
12
32
75
51
170
Mathematics and Computer Science Self-Study 74
Dr. Samuel Wiley
Course Number
CIS 623-BA
CSC 264-01
CSC 372-01
CSIT 136-01
Course Name
Fall, 2003
N-Tier Architecture
Data Base Management Systems
Database Applications
Intro to Info Tech
Credits
SCH
3
3
3
3
36
57
45
51
189
CIS 530-BA
CSC 152-21
CSC 265-21
CSC 265-22
Spring, 2004
Graphical User Interfaces
Intro CSC: Science Apps.
PC Applications
PC Applications
3
3
3
3
30
48
39
66
183
CIS 623-A
CSC 340-21
Fall, 2004
N-Tier Architecture
Database Applications
3
3
60
42
102
3
3
72
27
99
Spring, 2005
CSC 151-23
CSC 340-21
Fall, 2005
Intro CSC: Packages
Database Applications
Spring, 2006
Mathematics and Computer Science Self-Study 75
Appendix G: Advising Progress Report Form
Mathematics and Computer Science Self-Study 76
Name:
LaSalle ID:
Email:
Credits earned:
Overall GPA:
Est. Major GPA:
Transfer credits:
Major 1: INFT
Advisor:
Date:
97
2.74
2.42
3
Linked courses:
a. Double:
b. Double:
ENG 100 B F 03
PHL 151 B+ F 03
1. Powers
a. Writing I:
b. Writing II:
c. Numbers:
d. Speech:
e. Info. Tech.:
ENG 107 B Sp 04
ENG 108 C+ F 04
Waived
COM 150 B- Sp 04
Waived
2. Frameworks
a. Natural Sci.: Waived
b. Econ/Poli:
ECN 150 C+ Sp 05
c. Psych/Soc:
SOC 150 C+ Sp 05
3. Patterns
a. Religion I:
REL 153 * F 06
b. Religion II: ________________
c. Philosophy I: PHL 151 B+ F 03
d. Philosophy II: PHL 212 C+ Su II 05
e. Literature I: LIT 150 C+ F 05
f. Literature II: LIT 250 B Sp 06
g. History I:
HIS 151 B F 05
h. History II:
HIS 251 C+ Su II 05
i. Arts/Lang. I: ITL 201 A F 04
j. Arts/Lang. II: ITL 102 A- Sp 04
k. Concentr.:
________________
Other: ECN 150 W Sp 04
Generated on Wednesday, June 14, 2006
Major 2:
Major Requirements
Data Communic:
VB Programming:
Database Mgt:
OO Programming:
Comp. Architecture:
Computer Ethics:
Client Support:
LANs/Network Adm:
Applied Op Sys:
Information Security:
Required Internship:
Major Elective 1:
Major Elective 2:
Discrete Math 1:
Discrete Math 2:
Comp Electronics 1:
Comp Electronics 2:
General Elective
CSIT 136 B+ F 03
CSC 157 B+ Sp 04
BUS 204 * F 06
BUS 204 T F 02
BUS 101 C+ Sp 05
ENG 100 B F 03
ITL 101 A F 03
SOC 231 * F 06
FYO 100 A F 03
CSIT 220 C+ F 04
________________
CSC 240 B+ F 04
CSC 280 C- Sp 05
CSIT 301 C Sp 06
CSC 310 B- Sp 06
CSIT 321 B+ F 05
CSIT 320 B- F 05
CSIT 420 * F 06
________________
________________
CSIT 370 B- Sp 06
CSC 480 * F 06
MTH 160 C- F 04
MTH 161 D+ Sp 05
PHY 201 B- F 05
PHY 202 B Sp 06
Mathematics and Computer Science Self-Study 77
Appendix H: Exit Survey Results, 2006
Mathematics and Computer Science Self-Study 78
Exit Survey, Department of Mathematics & Computer Science
Spring, 2006
Major: Computer Science
How satisfied are you with the following aspects of the program?
The scale is 1 (very dissatisfied) to 4 (very satisfied).
Overall
Content of courses
Rigor of courses
Practicality of courses
Preparation for workplace
Number of specializations
Number of electives
Availability of courses
Scheduling for courses
Quality of facilities
Quality of equipment
Accessibility of faculty
Quality of teaching
Faculty attitude towards students
Faculty advising
Student to faculty ratio
Quality of fellow students
Responding to student requests
Preparation for job market
Breadth of coverage of topics
Depth of coverage of topics
Average
3.7
3.4
3.6
3.2
3.2
2.7
3.4
3.3
3.2
3.4
3.5
3.8
3.8
3.9
3.8
3.8
3.4
3.4
3.3
3.3
3.5
Please indicate where you think the program lies in terms of the following characteristics. The endpoints of the scale are described verbally, but you can use any point on the continuum between 1 and 5.
Easy admissions Standards
Theoretical
Easy
Boring
Outdated
Technologically backward
Low prestige among my colleagues
Very beneficial to my career
Very likely to increase my earnings
Workload is very light
Short program
Too general
Poor Teaching
2.9
2.8
3.5
3.3
3.5
3.2
3.9
2.9
3.1
3.7
3.6
2.9
4.0
Tough Admissions Standards
Applied
Hard
Intellectually-stimulating
Cutting-edge
Technologically advanced
High prestige among my colleagues
Not at all beneficial to my career
Unlikely to increase my earnings
Workload is very demanding
Long program
Too specialized
Excellent Teaching
If you had to do it all over again, would you have enrolled in this program?
Raw Data:
Definitely Not: 0
Probably Not: 1 Probably Yes: 7 Definitely Yes: 5
Would you recommend this program to a friend?
Raw Data:
Mathematics and Computer Science Self-Study 79
Definitely Not: 0
Probably Not: 1
What are your plans after graduation?
1 no definite plans
2
3
4
will start graduate studies in
September at:
may start graduate studies in the
future at:
Have accepted an employment
offer with:
Probably Yes: 8
Definitely Yes: 4
6
4
Drexel (1), LaSalle (3)
0
3
Lockheed-Martin, Protivity,
US Marine Corps
Mathematics and Computer Science Self-Study 80
Exit Survey, Department of Mathematics & Computer Science
Spring, 2006
Major: Information Technology
How satisfied are you with the following aspects of the program?
The scale is 1 (very dissatisfied) to 4 (very satisfied).
Overall
Content of courses
Rigor of courses
Practicality of courses
Preparation for workplace
Number of specializations
Number of electives
Availability of courses
Scheduling for courses
Quality of facilities
Quality of equipment
Accessibility of faculty
Quality of teaching
Faculty attitude towards students
Faculty advising
Student to faculty ratio
Quality of fellow students
Responding to student requests
Preparation for job market
Breadth of coverage of topics
Depth of coverage of topics
Average
3.6
3.6
3.8
3.2
2.8
3.2
3.4
2.4
2.6
3.4
3.4
4.0
3.4
3.6
4.0
3.4
3.8
3.4
3.8
3.0
3.6
Please indicate where you think the program lies in terms of the following characteristics. The endpoints of the scale are described verbally, but you can use any point on the continuum between 1 and 5.
Easy admissions Standards
Theoretical
Easy
Boring
Outdated
Technologically backward
Low prestige among my colleagues
Very beneficial to my career
Very likely to increase my earnings
Workload is very light
Short program
Too general
Poor Teaching
2.8
3.0
3.4
4.0
3.4
3.4
3.8
1.8
2.0
3.2
3.4
2.2
4.0
Tough Admissions Standards
Applied
Hard
Intellectually-stimulating
Cutting-edge
Technologically advanced
High prestige among my colleagues
Not at all beneficial to my career
Unlikely to increase my earnings
Workload is very demanding
Long program
Too specialized
Excellent Teaching
If you had to do it all over again, would you have enrolled in this program?
Raw Data:
Definitely Not: 0
Probably Not: 2 Probably Yes: 1 Definitely Yes: 2
Would you recommend this program to a friend?
Raw Data:
Mathematics and Computer Science Self-Study 81
Definitely Not: 0
Probably Not: 2
What are your plans after graduation?
1 no definite plans
2
3
4
will start graduate studies in
September at:
may start graduate studies in the
future at:
Have accepted an employment
offer with:
Probably Yes: 1
Definitely Yes: 2
2
The Vanguard Group
Protivity Corp.
Mathematics and Computer Science Self-Study 82
Exit Survey, Department of Mathematics & Computer Science
Spring, 2006
Major: Mathematics
How satisfied are you with the following aspects of the program?
The scale is 1 (very dissatisfied) to 4 (very satisfied).
Overall
Content of courses
Rigor of courses
Practicality of courses
Preparation for workplace
Number of specializations
Number of electives
Availability of courses
Scheduling for courses
Quality of facilities
Quality of equipment
Accessibility of faculty
Quality of teaching
Faculty attitude towards students
Faculty advising
Student to faculty ratio
Quality of fellow students
Responding to student requests
Preparation for job market
Breadth of coverage of topics
Depth of coverage of topics
Average
3.3
3.5
3.5
3.0
2.8
3.5
2.5
2.5
3.3
3.3
3.3
4.0
3.8
4.0
3.8
4.0
3.5
3.3
2.8
3.5
3.3
Please indicate where you think the program lies in terms of the following characteristics. The endpoints of the scale are described verbally, but you can use any point on the continuum between 1 and 5.
Easy admissions Standards
Theoretical
Easy
Boring
Outdated
Technologically backward
Low prestige among my colleagues
Very beneficial to my career
Very likely to increase my earnings
Workload is very light
Short program
Too general
Poor Teaching
3.0
3.0
3.5
4.0
3.8
3.3
3.5
2.3
3.0
3.0
3.3
3.3
4.5
Tough Admissions Standards
Applied
Hard
Intellectually-stimulating
Cutting-edge
Technologically advanced
High prestige among my colleagues
Not at all beneficial to my career
Unlikely to increase my earnings
Workload is very demanding
Long program
Too specialized
Excellent Teaching
If you had to do it all over again, would you have enrolled in this program?
Raw Data:
Definitely Not: 0
Probably Not: 1 Probably Yes: 2 Definitely Yes: 1
Would you recommend this program to a friend?
Raw Data:
Mathematics and Computer Science Self-Study 83
Definitely Not: 0
Probably Not: 1
What are your plans after graduation?
1 no definite plans
2
3
4
will start graduate studies in
September at:
may start graduate studies in the
future at:
Have accepted an employment
offer with:
Probably Yes: 2
2
1
Temple
0
1
AFLAC
Definitely Yes: 1
Mathematics and Computer Science Self-Study 84
Appendix I: Grade Inflation
Mathematics and Computer Science Self-Study 85
August 23, 2004
To:
Department Faculty
From: Linda Elliott, Tom Blum, Peggy McCoey
Re:
Grade Inflation
Grade inflation does exist, and it is a problem. It is our responsibility as faculty to address this issue.
As such, it is a legitimate criterion to raise when considering hiring, rehiring, tenure, or promotion.
Grade inflation is the increase in the average student GPA when it is unaccompanied by a
corresponding increase in average student quality or achievement. There is ample evidence for
increasing GPAs1 and none for increasing student quality (indeed it may be the reverse).2
Since grades have a ceiling, the increasing of grades implies a narrowing of the range of grades
typically issued. It is a tenet of Information Theory that if fewer states (grades in this case) are
available for occupation or even if fewer states are occupied on average, then less information is
conveyed. In short, grade inflation implies that grades are becoming less meaningful.
Grades provide data on students’ talents and comprehension of material. Students use this information
to make decisions about their futures. Similarly employers and graduate schools are using this data to
make decisions about students. We are shirking our duty and abdicating our role in these decisions.
It is unfair to those students who truly excel when excellent grades are given to almost all. It is also
unfair to the poor students who may remain in majors for which they are ill suited and who take away
the lesson that little is expected of them. It is the nature of La Salle’s mission and admission policies
to take a chance on some students, and taking a chance means there is a possibility for failure.
Eliminating that will turn the degrees we issue into little more than certificates of attendance. The
problem is not unique to the undergraduate programs, however. While La Salle’s mission for our
graduate programs is somewhat different, there is still a need to address this issue. In fact, it may be
more serious at the graduate level since the range of grades is smaller.
It is time that we recognize and accept the role of student evaluators and rededicate ourselves to it. We
need to have grades that are fair, that truly distinguish one student’s performance from the next, and
that are open so that students know what is expected of them and whether they have met these
expectations. Doing so will help the learning process not hinder it.
A step toward reversing the grade inflation trend is for each of us to examine his or her grading
policies and practices. The period before the semester begins, while we prepare syllabi and otherwise
prepare, is an ideal time for this reflection. We offer the following list of questions as a guide.
Checklist
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1
Am I covering the course material with sufficient breadth and depth?
For example, see the data on the website http://www.gradeinflation.com.
Henry Rosovky and Matthew Hartley, Evaluation and the SAcademy: Are We Doing the Right Thing?
http://www.amacad.org/publications/monographs/Evaluation_and_the_Academy.pdf
2
Mathematics and Computer Science Self-Study 86
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3
o Am I covering the course content agreed upon by the department as reflected in the
course description and generic syllabus?
o Have the students previously seen the material?
o Have students historically received unusually high grades in this course? (That is a
pretty clear indication that one could take it up a notch.)
Am I assessing the students enough?
o Do I have a sufficient number of tests, assignments, etc. to evaluate the students?
o Have I over-committed myself and resorted to decreasing the number of student
assignments as a measure of self-preservation?
Am I assessing the students rigorously?
o Are there assessment elements that even the good students will find challenging?
o Am I grading in a manner that produces a distribution of grades?
Am I evaluating the students individually?
o If there is a substantial amount of group work, is there individual assessment within
that? And do I have anyway to confirm an individual’s contribution to the group?
Am I assessing the students objectively?
o Have I laid out clear and objective criteria so that my grades are less susceptible to
argument?
Am I assessing the students in class?
o Am I relying too heavily on work done outside of the classroom where I must trust in
the student’s academic honesty?
Am I available enough to help the students?
o Am I “tough but fair” or just tough?
Am I pandering to students?
o Do I yield to students so that I receive good evaluations in return?3
o Do I yield to students who claim to need a particular grade to maintain a scholarship,
have work pay for the course, graduate, etc.?
There is a correlation between professor giving students high grades and students giving professor high marks on
evaluations. The Department of Physics and Astronomy at the University of Virginia added a question about the rigor of
the course on their evaluations in order to deal with this issue.