Project Narrative
Statement of Goals
Truman’s Data Mastery Initiative seeks “proof of concept” for an innovative approach to
competency-based learning in the vital field of data science by intervening at two ends of a pipeline of
students extending from pre-college learners, through traditional undergraduates, to adult learners
placed in industries vital to Missouri’s continued economic growth. Truman sees steps undertaken with
grant support to be the first steps toward expanded use of targeted competency-based learning
encompassing select disciplines and graduate programs, as well as possible future fulfillment of select
general education objectives. This approach to competency-based learning builds on existing
knowledge of other institutions with unique delivery and credentialing approaches with the potential to
greatly enrich student learning and achievement. The disciplinary focus is informed by consultations
with leaders in Missouri-based industries – such as MasterCard and Cerner – who underscore the value
of education in data science, as well as overall digital literacy, among their employees.
Premises
The initiative is premised on two important assumptions. First, that it is advantageous to move
exposure to computer science concepts to the secondary school level. This not only advances
awareness and reasoning skills among students, but it also accelerates students’ advancement into a
college-level computer science curriculum at a lower cost. Presently, Department of Elementary and
Secondary Education (DESE) graduation requirements do not include computer science, though it may
be exercised as an elective.1 Further, as dual credit policies require teachers at the partnering high
school to hold a Master’s degree with at least 18 graduate credit hours in the subject area,2 the prospect
for many schools – particularly in rural and underserved communities – to offer an affordable, quality,
concurrent enrollment experience in computer science, without significant instructional involvement
from the sponsoring university, is poor.
Second, the initiative recognizes the increasing need for qualified professionals to manage and
study “big data.” The employers of graduating computer science, mathematics, and actuarial science
students report that Missouri businesses have a critical need for employees in the newly emerging field
of data science. This initiative recognizes that a path is needed for advanced undergraduates, graduate
students, and adult learners in the workplace to develop competency in the field. The need for data
scientists – those who mine the massive volume of data generated by our networked world – is growing
rapidly. Prospects for employment are particularly bright in the coming years with the supply of
qualified practitioners expected to be outpaced by unprecedented demand. With a median salary in a
recent survey of $89,000, the job holds the prospect of rewarding employment opportunities
immediately upon graduation.3
Proof of Concept
1 http://dese.mo.gov/sites/default/files/Graduation_Handbook_2010.pdf
2 http://dhe.mo.gov/policies/dual-credit.php
3 http://www.itcareerfinder.com/it-careers/big-data-scientist.html
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The Data Mastery Initiative: Truman State University
It is important to underscore the significance of the phrase “proof of concept” in Truman’s
vision. Truman seeks to test and affirm several vital hypotheses for the advancement of competencybased education, at Truman, in Missouri, and elsewhere:
(1) That a competency-based methodology for education is not only compatible with, but supports
the goals and objectives of a highly-selective, liberal arts and sciences mission;
(2) That competency-based education can be effectively and reliably deployed at the secondary
school level in support of schools who might not otherwise be able to offer concurrent
enrollment experiences, while still maintaining or enhancing quality;
(3) That the use of “digital badges” affords learners a tangible, granular counterpart to the
traditional course-based model of credentialing, that improves prospects for gainful
employment, empowers employers in the search for qualified employees, and increases
flexibility in students’ exploration of subjects that interest them.
Broad Learning Objectives
Across all aspects of the initiative, Truman aims to:




equip a larger body of students with foundational knowledge in computer programming;
develop in students improved computational reasoning skills;
develop awareness of the importance of systematic study of data and its application to fieldspecific needs;
provide students with the confidence and adaptive capacity to apply programming and
analytical skills and concepts in workplace settings.
Significance for Time to Graduation and Cost Savings
In the marketplace of technological jobs, time is money. The rapid pace of change requires
responsive thinking about teaching and learning that nurtures personal exploration and inquiry,
encourages intellectual risk-taking, and rewards students for gains made inside and outside the
boundaries of the traditional “class.” Leveraging advantages of the self-paced, competency-based
learning model, delivered principally online, Truman aims to reduce the costs of learning through
economies of scale and accelerated time to completion, while empowering students to complete
learning at a pace appropriate to their life circumstances. The Data Mastery Initiative aims to engage
audiences at multiple levels to maximize timely advancement:



At the pre-college (primary and middle school) level targeted students will be engaged in
fundamental concepts in computer science through summer and weekend enrichment
programs designed to feed the hunger to learn. Earning non-credit digital badges, young
students’ autodidactic impulses will be fueled by personal accomplishment as they are exposed
to basic programming concepts and encouraged to seek tangible symbols of their success.
High school concurrent enrollment courses will provide students an opportunity to earn lowcost college credit in computer science (CS 170 – Introduction to Computer Science I), obviating
the need for the course at college. For non-majors, coursework will affirm basic skills appealing
to future employers while fulfilling pre-requisites for college electives in computer science.
Graduate certificate courses in data science will be offered in an entirely competency-based
format. Coursework will be transcripted in a traditional, credit hour-based framework (a
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The Data Mastery Initiative: Truman State University

required set of four or five courses), but delivered in a self-paced, online format and assessed
through state-of-the-art, proctored competency examinations.
A suite of digital badges, displayed via an open badges portfolio infrastructure, will overlay all
courses in the initiative. Completion of competencies, authenticated by summative
assessments, will be recorded in a manner enabling employers to appreciate job candidates’
competencies granularly. In turn, because of the modular framework of coursework, badges
can be offered independently as stand-alone competencies for low cost, professional
development opportunities. This concept of overlaying badges on top of a course-based
structure makes the model truly distinct from existing approaches.
Competency Identification and Curriculum Development
Truman envisions a process of curriculum development targeting Missouri business needs, while
drawing on faculty subject matter expertise, to ensure critical competencies are met. While the
curriculum for CS 170 must be grounded in the objectives of the larger Truman computer science
curriculum, and general education objectives, businesses will be consulted to identify those skills most
needed from their employees. This conversation can inform the re-examination (if needed) of larger
curricular objectives in the major with an eye toward assuring that the introductory course assesses
business-supportive competencies and the major appropriately prepares students for advancement,
should they choose, into the graduate certificate sequence.
The more vital component of this conversation relates to uses of data science in business
operations. For the graduate certificate to be meaningful, it is critical that planners appreciate those
skill sets vital to employers. Further, as competencies within the curriculum are isolated for creation as
stand-alone badges, it is equally important for Truman to identify those competencies employers
believe might constitute important professional development opportunities.
Overlaying competencies identified in this conversation onto coursework, faculty will map
courses to ensure that both faculty-determined and employer-identified competencies are addressed –
determining which competencies are sufficient to stand on their own as discrete, assessable skills (which
could function as “badges”) and those which may be bundled together into larger groupings of content.
Once the curriculum of the courses is mapped, Truman faculty will design self-paced learning
modules, film lectures and demonstrations, curate fee and open-source learning objects, create
exercises, and build assessments aimed at evaluating content understanding. An important objective of
this design is to ensure that, where appropriate, individual skills that can be learned and assessed
independently of broader courses, are consciously developed as stand-alone badges.
Organizational Framework and Partnerships
The project will be coordinated by Truman’s Institute for Academic Outreach and the Dean of
the School of Science and Mathematics, with curricular and instructional leadership by the Computer
Science department, in consultation with faculty in other relevant departments who have expertise in
data science. Business partners will be asked to provide advisory committee representatives as well as
contribute ideas for field-specific, learning activities for students participating in initiative coursework.
MasterCard has already agreed to provide representation on such a committee, and we are confident
other Missouri corporations with data science interests will follow suit.
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The Data Mastery Initiative: Truman State University
Courses, Curricula, and Experiences
As presently envisioned, the Data Mastery Initiative will include:



A 100-level introductory computer science course (CS 170) offered to both high school and
selected undergraduate sections;
At least four or five initial 500/500G-level courses in data science offered to graduate students
seeking a certificate in data science and available to advanced undergraduate students;
Within data science coursework and CS 170, multiple non-credit, digital badges representing
embedded, specific, notable skills.
All of the aforementioned courses will be competency-based and will be “modularized” to provide for
topic-specific badges and assessments for sub-categories of course content.
In addition, existing and anticipated programming targeted at gifted middle school students will be
developed with competency-based components for which students can earn badges and develop
inspiration for further study. These additional learning experiences, while part of the broader initiative,
will fall outside of the scope of funds requested in this grant, but will be designed to “prime the pump”
of aspiring students entering a computer science/data science pipeline. These additional programs
would include:


A Java language course for students at Truman’s Joseph Baldwin Academy (JBA).
An elementary mobile application development course at JBA.
Partner Roles in Establishing Competencies
Given the process for identifying competencies and developing the curriculum described above,
the role of business partners in isolating critical knowledge and skills is important. Partners will play a
vital role in identifying those competencies key to student success at work. Additionally, partners will
play a role in inspiring students at our secondary school partner institutions. In particular, Truman will
seek to pair businesses with concurrent enrollment schools, affording students early exposure to
industry applications via project-based learning - amplifying concepts explored in class. Truman will also
encourage partner businesses to provide technological support where it may be needed.
Evaluating Competencies
Competencies will be assessed using formative and summative assessments. Formative
assessments will be aimed at measuring satisfactory progress toward understanding portions of
material covered in summative assessments, those assessments that definitively establish
competencies. In instances where understanding of smaller portions of material is pre-requisite for
advancement to other concepts, students will need to demonstrate a satisfactory level of
comprehension in order to move on to additional concepts of the course.
Monitoring Knowledge Acquisition Toward Assessment
By analogy, it is useful to think of a construction process. In constructing a building, one cannot
hang drywall or layer bricks until first framing the structure with timber or steel. Likewise, multiple
formative assessments help a teacher determine whether a student has constructed sufficient cognitive
4
The Data Mastery Initiative: Truman State University
scaffolding in order to complete construction of a particular segment of a larger knowledge structure –
represented by a summative assessment. To successfully complete a course, students will be required
to complete at least one, but typically multiple, summative assessments determining whether or not a
student has achieved competency or mastery of the subject matter represented by a course. For
individual badges, which represent a smaller body of content, competency will be measured by
demonstrating mastery on a single summative assessment.
Competency versus Mastery
Evaluation in a competency-based framework is premised on the notion that one can establish a
benchmark against which a student may be judged, by experts in the field, to possess the knowledge
and skills necessary for scholarly and professional effectiveness. Typically, “competence” is evaluated
by means of assessments that determine whether a student has met minimal desired expectations for
understanding or application of a particular, defined body of knowledge. For purposes of this project,
however, Truman intends to differentiate two levels of competence: competency and mastery. This
bifurcation of the body of competent learners is aimed, first, to remain consistent with Truman’s highly
selective identity and reputation of excellence. Second, the split is premised on the notion that certain
fields – particularly fields requiring computational precision – demand mastery, not merely sufficiency.
Faculty Role and Professional Development
Truman anticipates hiring one additional faculty member to support the work of designing,
implementing, and evaluating the proposed curriculum. Existing faculty will also be engaged in the
project and compensated for overloads and summer work. Hired faculty may share in teaching
responsibilities in order to allow existing faculty to spend more time on the project. Because
competency-based learning is in relatively limited use on Truman’s campus presently, involved faculty
will explore literature on current and best practices in competency-based education while collaborating
with industry partners to determine whether course content meets employer needs and working with
Truman’s instructional design team to produce high quality learning objects. High school faculty working
with concurrent enrollment courses will be engaged in a week-long, on-campus professional
development program aimed at equipping them to advise students, organize and conduct knowledgebuilding and applied problem solving exercises, and proctor assessments. The opportunity to take the
entire CS 170 course – in its competency-based format – will also be made available to high school
faculty at no cost.
Selection, Enrollment, and Evaluation of Students
Eligibility
Students selected for middle school programs will be identified by recommendations from their
middle school counselors. Those students selected for high school concurrent enrollment courses will
be required to satisfy any state-mandated minimal criteria for enrollment. All regularly-matriculated
Truman students will be eligible for the on-campus equivalent of CS 170 and all advanced
undergraduates will be eligible for data science coursework with the support of their academic advisor.
Graduate students will be eligible for graduate certificate enrollment via normal graduate certificate
application procedures, stipulating a minimum 3.0 GPA, completion of an application, satisfaction of any
prerequisites, and submission of undergraduate transcripts. Non-degree-seeking students may apply for
courses at the undergraduate or graduate level. Application to non-credit badging programs will be
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The Data Mastery Initiative: Truman State University
open to students of any level or experience, but a list of recommended pre-requisite learning
experiences will be published.
Evaluation of Students
As currently envisioned, students enrolled in our concurrent enrollment course, as well as our
graduate certificate courses, will be deemed “competent” if they have earned the equivalent of a B or
better on each of the summative assessments in the course. If the average of their summative
assessment grades in the course is equivalent to a B (80% or higher), they will be deemed “competent”
in the course. They will have achieved “mastery,” however, if they average the equivalent of an A (90%
or higher). To illustrate, if a student needed to take each of three assessments two or three times before
achieving satisfactory understanding, only the top grade for each summative assessment would be
considered in determining the average for the final course grade. A student would not be able to
average the scores from different sittings of the same summative assessment to determine the score for
that particular assessment. Upon successful completion of all summative assessments for the course at
the level of B or better, the student is deemed competent for the entire body of work, and all of the
badges therein. A grade of A or B will be entered on the student’s regular Truman transcript, reflecting
the average of the best scores on each of the summative assessments in the course.
A part of this initiative will involve exploration of the technical requirements for transcripting
competencies within the existing Truman registration and grading system, without making the record
dependent on entering letter grades (i.e.: A, B, or F) and, instead, allowing the entry of marks of
competency (i.e.: Competency, Mastery). At the undergraduate level, the necessity of computing a
grade point average will require the entering of a letter grade on the academic transcript. However, at
the graduate level, the goal will be to record all marks as statements of competency or mastery.
“Grading” and Representing Competencies. For full courses, a transcripted grade will be either
an A or a B and will be issued based on the average score of multiple summative assessments, with a B
(80%) constituting “competency” and an A (90%) constituting “mastery.” Grades and competencies are
not assigned based on any work in the course other than summative assessments. Homework, reading,
lab assignments, etc., will vary and will be designed as a means toward completing competencies. How
quickly a student grasps content, or how much prior knowledge a student brings, may change how much
preparatory work/study the student must complete before advancing to a summative assessment.
An example in Truman’s only existing competency-based courses is illustrative here. As part of a
ground-breaking initiative to bring concurrent-enrollment opportunities to students presently unable to
obtain them, Truman has been using a competency-based model for delivering college algebra and
plane trigonometry to high school students since an initial pilot in 2010. Truman uses the same
methodology for its equivalent introductory courses (MATH 156 and MATH 157) for undergraduates.
MATH 156 is Truman’s college algebra course. Using software developed by Hawkes Learning
Systems, students work practice problems representing individual concepts in algebra. While studying a
concept – let’s say, quadratic equations – students work on as many problems as necessary until the
computer has determined the student fully understands the concept. The student must achieve this
understanding, as well as grasp other concepts covered by a particular summative assessment, before
they are permitted to continue to one of three summative assessments in the course. When ready, the
student reports to a proctored testing environment where they complete a computer-administered
exam proctored by a classroom teacher. If students achieve a minimum score of 70% they are deemed
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The Data Mastery Initiative: Truman State University
“competent” on that summative assessment; but they may also retake that summative assessment
(with different problems) to score higher. The student must receive a score of 70% or higher on each
summative assessment in order to complete the course. If the student fails to complete any single
assessment at the level of 70% or higher they are deemed not competent and have “failed” the course.
Their final grade in the course is set by the average of the top scores on the three summative
assessments. In order to facilitate a truly self-paced experience, and to afford students the opportunity
to improve themselves toward competency, or greater mastery of the content, Truman has an
agreement with participating schools that students may continue to retake the summative assessments
– even if the semester of the initial offering is over – until the end of the school’s academic year. The
vast majority of students who complete the course do so with grades of A or B and the drop/failure rate
is quite low. Some students are able to complete the entire course – and all its assessments – in a
matter of days, while other students may need the entire academic year to complete the work. In these
courses, a grade of C has been deemed competent because that grade is typically considered acceptable
for advancement to subsequent coursework in a traditional undergraduate math curriculum.
As Western Governor’s University and the University of Wisconsin have demonstrated in their
models of competency-based learning, in more advanced coursework, or in instances where a student is
known to have prior knowledge from life experience, an advisor can guide students through the
necessary preparatory steps to perform well on a competency assessment without technology making
that judgment. While the Hawkes software used in our math courses requires students to complete at
least some practice problems to assess readiness for an assessment, readiness in other subjects might
require approaches similar to those used in the WGU or UW models – assessments ranging from essays,
to portfolios, to applied learning exercises – and will be informed by the expertise of teachers and
professors who can advise students of when it is appropriate to sit for an assessment.
Timeframe
Students may retake the summative assessments as many times as necessary to establish
competency, or mastery of content, up through the conclusion of a defined time period. Students failing
to complete all assessments at the level of B or higher by the end of the academic year (for secondary
schools) or within a calendar year of starting the course (for graduate and non-degree seeking students)
will be assigned an F on their transcript, but will retain any individual badges earned for the course.
Badging
Digital badges will be awarded for successful completion of each summative assessment, which
will be seen as a tangible indicator of established competency in a defined area of knowledge or skills
within a larger course (see Appendix A). Badges will be named to be descriptive of the content they
represent and recognizable to an employer. Badges will be transcripted on one of several open badges
portfolio platforms, independent of the Truman academic transcript, and will consist of “tiered” badges
representing the differentiated levels of competence – either competency or mastery.
It is entirely conceivable that a student completing a course in which they do not earn an A or B
might earn credit for one or more badges, having achieved competency/mastery in a particular body of
content, but not having achieved competency in the entire content of the larger course. Empowering
students to earn badges, even in circumstances where they may not have attained competency in a
course, leaves students with tangible measures of accomplishment that can be shared with employers.
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The Data Mastery Initiative: Truman State University
In addition, having established competency or mastery of one or more summative assessments will give
students a “leg up” on later completion of the entire course should they reattempt it.
In our middle school summer academies, digital badges will also be awarded. Here, badges will
motivate future study and assist counselors in measuring student readiness for concurrent-enrollment.
Methodology and Process for Evaluating Outcomes
Evaluation of the efficacy of this initiative will occur on two levels: student learning and proof of
concept. This evaluation will be conducted by a working group of faculty and administration, in
consultation with business partners. In absence of a control group for the graduate certificate, learning
in that program will initially be assessed by monitoring the percentage of students achieving
competency/mastery, as well as the pace at which students reach that point. At the undergraduate
level, the initiative will be particularly interested in comparing success rates of concurrent enrollment
students with those in traditional and competency-based sections of CS 170 offered on campus.
Because the ultimate success of the initiative is dependent on proving that the concept of a
competency-based concurrent enrollment program, and a competency-based graduate certificate with
an overlaying system of badges, can provide valuable alternatives that are rigorous and accepted by
even highly selective institutions, such as Truman, significant attention will be devoted to measuring the
efficiency of the program. Among the questions that will need to be answered include:
(1)
(2)
(3)
(4)
Does the program work efficiently as a concurrent enrollment experience?
Do students achieve competency at a rate faster than students in a traditional course?
Do employers appreciate the documentation represented by badges? Are they meaningful?
Is the university able to achieve cost efficiencies that can translate into less costly delivery?
In addition to monitoring trends in student performance, and trends in time to completion,
these questions will require evaluation of cost per student over time. Perceptions of program
effectiveness and efficiency by students, teachers, administrators, high school parents, and employers
will be sought through survey and focus group research to evaluate and modify the program.
Timeline for Implementation
The following represents the anticipated timeline for the completion of key tasks in the initiative.
Lettered certificate courses are placeholders for courses yet to be assigned formal names.
December 2014
Spring 2015
Summer 2015
Fall 2015
Spring 2016
Summer 2016
September 2016
8
Seek and hire instructional designer; seek and hire new faculty member.
Develop first half of each of graduate certificate courses A, B, C, and D; develop
first half of CS 170.
Develop second half of the graduate certificate courses A, B, C, and D; develop
second half of CS 170.
Deploy graduate certificate courses A and B; deploy CS 170; develop first half of
graduate certificate course E.
Deploy graduate certificate courses C and D; continue deployment of CS 170;
develop the second half of graduate certificate course E.
Deploy graduate certificate course E; deploy CS 170.
Evaluation and final report.
The Data Mastery Initiative: Truman State University
Number of Students Involved
The number of high school students involved in the competency-based CS 170 course will
initially be small in the proof-of-concept phase of the initiative. In particular, because very few Missouri
high schools have faculty qualified to assist in the delivery of a computer programming course, a key
challenge of this initiative will be to develop a framework that will scale to reach our target of 200
students in an efficient, cost-effective, sustainable way. Truman’s experience in competency-based
education in math suggests a population of 350-400 students in the proposed concurrent enrollment
course is eventually possible, with growing numbers over time.
Students in the Computer Science major constitute over 190 students and it can be anticipated
that a growing number of advanced students, as well as qualified students from several other
disciplines, may elect to take 500-level coursework in data science, or embedded badges, as they
become available. The ultimate goal is to encourage graduates and adult learners to pursue graduatelevel learning in data science, adding an additional layer of students that would likely initially measure in
the dozens, but could eventually scale to serve many more. The competency-based model, and selfpaced learning, provide for an on-demand delivery approach, allowing a larger number of students to be
served at a pace not rigidly governed by strict semester start and stop times. Because content is
principally delivered online, a greater number of students can be served efficiently and responsibly.
Sources and Amounts of Matching Funds
Truman anticipates that it will contribute financially, and in-kind, to several aspects of this
initiative, including aspects outside of the scope of the grant that are not strictly competency-based
(such as summer and weekend academies for youth aimed at starting an interest pipeline). At present,
Truman anticipates contributing at least $70,000 in cash and in-kind resources to the project – not
counting indirect costs. As industry partners are critical in understanding the learning objectives that
best serve their present and future employees, Truman hopes to enlist partners to help equip K-12
institutions participating in Truman’s pre-college badging and concurrent enrollment initiatives, as well
as provide continuous input on project-based learning that can reinforce comprehension of concepts
introduced online. While the contributions of business partners are not identified by dollar amount,
Truman is optimistic, based on initial conversations, that partners will find this opportunity attractive.
Relevance to Missouri Strategic Initiative for Economic Growth Priority Occupational Clusters
Digital literacy skills are critical to a broad range of Missouri industries – particularly those
identified in the Occupational Clusters of the Missouri Strategic Initiative for Economic Growth. The
foundational capacity to think in programming terms – irrespective of language system – informs much
wider critical thinking skills common to all of the disciplines identified. However, development of a
broader understanding of programming – specifically, the advanced skills of data science – clearly touch
on every cluster identified in the Missouri Strategic Initiative. Data science informs decision-making in
commerce, health care, energy, logistics, and more.
Organizational Capacity
Truman State University has been experimenting with a competency-based model of math
education for several years. All students taking college algebra and plane trigonometry now take the
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The Data Mastery Initiative: Truman State University
course using a self-paced approach. Similarly, the University’s Pre-Calculus course (MATH 186) has
recently begun experimenting with a competency-based model as well. This same model has been
employed successfully at high schools for four years, serving more than 1000 students. These courses
have experienced lower rates of withdrawal or failure and extremely high rates of students earning As
and Bs. Truman has learned a great deal from these experiences about how to manage student, parent,
and faculty expectations and motivations in a competency-based environment. The experience has also
been informative regarding how competency-based models can achieve greater time and cost
efficiencies. Computer-science represents a logical next step in the evolution of this approach, given the
similarity of skill sets and assessment techniques. The department’s faculty are very eager to
participate, and are particularly excited about the prospects for meeting Missouri’s data science needs.
Truman is excited to use this experience to tackle a new disciplinary area. Because learning
computer programming is very different from learning mathematics, in a number of substantial ways, a
significant amount of research and development will be required to replicate Truman's success in
competency-based mathematics courses.
Organizationally, the University’s Institute for Academic Outreach has administered the existing
math program and has studied competency-based approaches for the last several years with an eye
toward eventual expansion of the concurrent enrollment program. Further, with its responsibility for
distance education, the Institute is the office on campus most familiar with existing experiments in
competency-based learning. The office is well-prepared to lead this endeavor.
Plans for Sustaining, Expanding, and Sharing the Project
Truman is confident that revenue generated by the initial course offerings will be sufficient to
make the initiative self-perpetuating. Truman is positive that the knowledge and revenue generated will
be the basis for expanding the number of courses using this approach and developing similar
coursework in disciplines that are ripe for it. In particular, Truman envisions the development of
additional graduate certificates using the model. On the concurrent-enrollment level, Truman firmly
believes that a competency-based model is essential for helping schools provide early college
experiences in areas where qualified teachers are atypical and where resources simply are not available.
Recognizing the importance of this work for the cause of education in Missouri, as well as the
importance of enhanced preparation of graduates for the workplace, Truman intends to disseminate the
results of the pilot project to its secondary and post-secondary peers throughout the state by inviting
representatives to a short conference at the conclusion of the pilot and by sharing documented results
to all institutions inquiring about the approach.
Recognizing the importance of this work for the cause of education in Missouri, as well as the
importance of enhanced preparation of graduates for the workplace, Truman intends to disseminate the
results of the pilot project to its secondary and post-secondary peers throughout the state by inviting
representatives to a short conference at the conclusion of the pilot and by sharing documented results
to all institutions inquiring about the approach.
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The Data Mastery Initiative: Truman State University
Appendix A
Badges Nested in Coursework
Badges are awarded for successful
completion of summative
assessments which each represent
completion of one portion of the
larger competency represented by
the course.
Graduate Certificate
Badge
Competency
A
Badge
Competency
C
Badge
Competency
D
Badge
Competency
F
11
Badge
Competency
B
Badge
Competency
E
Badge
Competency
G
The Data Mastery Initiative: Truman State University
Class
Class
Class
Class
Appendix C
Line Item Budget
Administrative, Faculty, and Staff Costs
Item
Grant Cost
University Cash
University In-Kind
Notes
Faculty # 1
1/2 Year Salary (Jan. 1 - May 31)
$30,000.00
Summer Stipend
$10,000.00
AY 2015-2016 Salary
$60,000.00
FICA and Benefits
Summer Academy (JBA) Instructional Salary –
Summer 2016
Summer Academy FICA and Benefits – Summer
2016
$35,000.00
Annual FICA & Ben .35
$4,300.00
$1,075.00
Summer FICA & Ben .25
Instructional Designer
12 Month Salary (Jan. 1, 2015-Jan. 1, 2016)
$50,000.00
6-Month Extension (Jan. 1, 2016-June 30, 2016)
FICA and Benefits
$25,000.00
$17,500.00
$8,750.00
Annual FICA & Ben. .35
Student Employment
Student Employment
$30,800.00
$7,800.00
Student Employment FICA
2356.20
$596.70
Equivalent of 1 FTE x 52 weeks x $7.50 (Institutional and
Scholarship Workers)
Student Recruitment and Marketing
Printed Literature
$2,500.00
Online Marketing
$30,000.00
Promotional materials for high schools and certificate
candidates
Online marketing for graduate certificate and badges
Apprenticeships and Student Stipends
Tuition Waiver for High School Faculty to Take
CS 170
$14,985.00
$999 for 3 credits x 15 students
Curriculum Development
Faculty Travel to Coordinate with Businesses
$5,000.00
Course Development Stipends - CS Faculty
$48,000.00
8 stipends at $6000 each
Summer FICA and Benefits
$12,000.00
Summer FICA & Ben .25
High School Faculty Training Workshop
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The Data Mastery Initiative: Truman State University
Housing in West Campus Suites
$2,625.00
5 nights x 15 participants
Meals for Workshop Participants
$2,250.00
6 days x 15 participants x $25
$3,000.00
$200 x 15 participants
Transportation Reimbursement
Supplies and Materials
Instructional Design Technology and Support
$70,000.00
Lecture Capture Equipment and Software
$30,000.00
Upgrade course studio recording software and hardware;
learning management platform support and maintenance;
collaborative tools support; technical support; storage
support and backup; course badging infrastructure; etc.
Video production assistance; video storage, software
support.
Totals
Totals
$400,000.00
$95,141.20
$0.00
Budget Narrative
Recognizing the significant up-front costs of course redesign, the chief expenses in the proposed grant budget are located in salaries for course
development and deployment, and in instructional design services. This proposal identifies the need for a full-time faculty member in computer
science (or the equivalent in replacement faculty time) and 18 months of instructional design services. It is expected that the process of building
multiple new courses and modules in a competency-based format, during the compact timeframe of the grant, will require the full-time
attention of at least two individuals. Additionally, this budget commits the equivalent of a single, full-time student assistant (likely in the form of
multiple part-time individuals) to handle such functions as lecture capture, video editing, content research, and curation of web-based
resources. Additional funds are dedicated to summer stipends for computer science faculty to work on module development.
The budget includes funds designed to provide the technological support needed to build high quality, on-demand learning modules. This
includes hardware and software upgrades, possible investment in commercial platforms for course delivery, video production equipment and
storage hardware, and possible personal augmentation to manage the technology.
For the planned concurrent enrollment course (CS 170) the budget includes funds to hire upper-level computer science undergraduate students
to serve as tutors and virtual lab assistants. It is easy for a beginning student be stuck for hours over a simple error. For the experiment in
developing this concurrent enrollment course to scale, student tutors will greatly expand the reach of each faculty member.
Because these courses involve active programming exercises, students will be expected to use computers and view only content. Where
computers are available at home, or in their school, these activities can be conducted without additional equipment. However, Truman intends
to engage corporate partners to encourage them to outfit select pilot schools in the concurrent enrollment portion of the program with updated
equipment.
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The Data Mastery Initiative: Truman State University
The budget is rounded-out with modest expenditures in marketing, which will be supplemented by marketing spending from Truman’s Institute
for Academic Outreach.
Truman anticipates a sizable contribution of its own resources in real dollars and in-kind (scholarship worker) contributions.
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The Data Mastery Initiative: Truman State University