Examining Technology Adoption by Mathematics Professors
Joyce Asing-Cashman and David Rutledge
New Mexico State University
United States
jcashman@nmsu.edu
rutledge@nmsu.edu
Abstract: This case study examined four mathematics professors technology adoption at one
university. The three stages in which university faculty moves in the technology adoption process
suggested by Celsi and Wolfinbarger (2002) was used to determine the mathematics professors
level of technology adoption. Results indicated that three mathematics professors demonstrated as
“initial” users of technology. A more “engaged” or constructivist approach was demonstrated by
one mathematic professor where he encouraged his students to be active learners. He modeled the
use of technology in the lab to facilitate active learning where the technology (computer and
Mathematica program) involves student interaction with the content that allows knowledge
building and construction.
Introduction
As higher learning institutions prepare future teachers to teach in the 21st century, future teachers need to
be equipped with the tools to meet the needs of understanding technology and its applications (Bitner & Bitner,
2002). Teachers can use technology resources to provide opportunities for learning and create the “conditions that
optimize learning” (Jonassen, Howland, Moore & Marra, 2003). Technology provides the means for the teacher to
re-examine the nature of the classroom environment. In mathematics, groups such as Mathematics Association of
America (1991), Mathematical Sciences Education Board (1991); and National Council of Teachers of Mathematics
(NCTM) (2000) recommend using technology as a valuable tool for mathematics instruction, and a tool for
supporting students’ mathematical explorations. The current notion is that available technology can and should
change how mathematics is taught and how it is learned (Heid, 1997). Thus, technology has the potential to engage
students more fully in mathematical thinking and learning, and provides students access to more advanced
mathematics. In The Principles and Standards for School Mathematics, the NCTM (2000) states that “technology is
essential in teaching and learning mathematics; it influences the mathematics that is taught and enhances learning”
(p. 3). Technology use by teachers should be encouraged at early levels, beginning in kindergarten and extending
throughout students’ mathematics education (NCTM, 2000).
The success of technology infusion in the schools depends partially on both in-service and pre-service
teacher development. In the near future, public schools will require teachers to have competent technology skills and
be able to effectively implement technology in classrooms (Leatham, 2007). It is plausible to require pre-service
teachers to incorporate technology into the lessons they prepare to teach (Johnson-Gentile, Lonberger, Parana, &
West, 2000) as teacher education programs help them to prepare for their future classrooms. Teacher preparation
programs must provide prospective teachers opportunities to learn important skills and examine pedagogical issues
for using technology in classrooms. This entails the need to employ technology tools in the preparation of
mathematics teachers by mathematics professors. Consequently, mathematics professors need to have strong
comfort level with, and consistently employ, technology tools as part of their own repertoire of tools in mathematics
teacher education courses. A growing number of studies have shown that technology has the potential to positively
affect the teaching and learning of mathematics at various levels of the education system, even though this has not
been widely realized in schools and Institution of Higher Learning (Artigue, 2002; Lavicza, 2006, Pierce and Stacey,
2004). In contrast to the large body of research focusing on technology usage that exists at the secondary school
level, there is a definite lack of parallel research at the university level. However, Lavicza (2008a) highlights that
university mathematicians use technology at least as much as school teachers, and that the innovative teaching
practices involving technology that are already being implemented by mathematics professors in their courses
should be more fully researched and documented. Further, Lavicza found that within the research literature there
existed only a small number of papers dealing with mathematicians and university-level, technology-assisted
teaching. In addition, most of these papers are concerned with innovative teaching practices, whereas few deal with
educational research on teaching with technology. This study sought to examine the extent of technology adoption
by university mathematics professors in one university in their mathematics classroom.
1
Theoretical Framework
Several models of educational technology adoption were developed trying to understand and facilitate
faculty technology adoption process. Two of the most popular models are Rogers’ (2003) Diffusion of Innovations
and Concerns-Based Adoption Model (CBAM) (Sherry & Gibson, 2002). To better understand the level of
technology adoption, Rogers (2003) described five variables: perceived attributes, type of innovationdecision, nature of communication channels, nature of the social system, and the efforts of change agents. In
addition to Rogers’ (2003) diffusion theory, Hall and Hord described another adoption model, the CBAM
model, in which they enumerated eight different levels of use of an innovation: nonuse, orientation, preparation,
mechanical use, routine, refinement, integration, and renewal. Celsi and Wolfinbarger (2002) suggest that adoption
of innovation patterns by university faculty moves through three stages: (1) technology as a support function not
significantly affecting teaching; (2) technology used in teaching but with little significant classroom change; and (3)
technology use results in fundamental change in classroom structure and behaviors. Realizing the large numbers of
factors influencing technology adoption, another adoption model, the Learning/Adoption Trajectory model,
developed by Sherry, Tavalin, & Gibson (2000) emphasizes moving through five stages of change and the
importance of support and a shared vision by educational system members. This model uses a cyclical rather than a
linear process and is a research-based model established on a five year project with teachers in Colorado (Sherry,
1997, p. 68). Although, the Learning/Adoption Trajectory model was created to evaluate K-12 teachers’ technology
use level, this model was successfully used in describing the level of higher-level faculty technology use in a
research study conducted by Hagenson (2001).
Method
A case study was employed in this study. Merriam (2002a), articulated that case study is an examination of
a specific phenomenon such as group, a program, an event, a person, a process, or an institution. Case study
researchers immerse themselves in the totality of the case. As the setting becomes familiar, and as data are collected,
the researcher looks for underlying patterns of conceptual categories that make sense. Case studies are usually
inductive in nature. Descriptive case studies make extensive use of qualitative data (Merriam, 2002a) by drawing on
multiple sources of information such as interviews, observations, documents, and audio-visual materials (Creswell,
1998). Qualitative case studies for this project rely heavily upon qualitative data obtained from interviews,
observations, and documents.
There will be inherent limitations related to the nature of this study. The primary instrument in any case
study is human, therefore, all observations and analyses are filtered through individual values and perspectives of
the researchers, who must be aware of how they may skew and shape what they hear, see, and understand (Stake,
1995). Triangulation will be used in this study in the form of in-depth interviews, observations and document
reviews. This study combined two types of interview. The guided interviews included open-ended questions that
were asked to all participants, and some time in each interview there will be time spent in an unstructured mode so
that fresh insights and new information can emerge (Merriam, 1998). In an effort to minimize the distortions on the
researcher’s part, as the interviewer, and on the interviewees, we tried to be neutral and nonjudgmental. The
researcher refrained from arguing, tried to be sensitive to the verbal and nonverbal messages conveyed, and made
every effort to be a reflective listener (Stake, 1995). Although, both parties will bring biases, predispositions, and
attitudes that color the interaction and the data elicited, the interviewer accounted for these factors in an effort to
extract worthwhile information. In addition, plans for the researcher or the participants can change at any time,
leading to difficulty in completing the research as planned.
Participants
All four participants were mathematics professors that teach required courses for secondary level preservice mathematics teachers, and are attached with the Department of Mathematics at a university. These
participants were given the following pseudonyms: Dr. Hunt, Dr. Grant, Dr. Blum, and Dr. Till (See Table 1).
Table 1: Participant’s demography
Dr. Hunt
Dr. Grant
Dr. Blum
Dr. Till
Gender
Male
Male
Male
Female
Teaching
Experience
25 years
17 years
20 years
17 years
2
Course
Taught
Numerical
Analysis
Introduction to
Higher
Mathematics
Matrix
Algebra
Matrix
Algebra
Number of
3
3
3
3
Observations
Data Sources
Interviews. Patton (1990) stated that the purpose of the interview is not to put things in someone else’s
mind but rather to access the perspective of the person being interviewed. Therefore, in this study, semi-structured
interview was conducted to deeply explore the participant's point of view, feelings and perspectives. A semistructured interview is an open-ended, discovery-oriented method that is well suited for describing processes and
outcomes in implementing technology from the perspective of mathematic professors. Approximately 45 minute
individual semi-structured interviews were conducted. A pre-interview was conducted with each mathematics
professors, and a post-interview subsequent to conducting direct observation in the respective mathematics
professor’s class. An interview protocol, a predetermined sheet of the sixteen open-ended questions allowed the
researcher to take notes during the interview, and help organize thoughts on items such as headings, information
about starting the interview, concluding ideas, information on ending the interview, and thanking the respondent. All
interviewees received the same set of interview questions. A digital voice recorder was also used to help collect
accurate information from the interviewees.
Observations. Observations are considered essential in qualitative research. They provide the researcher
with a rich understanding of the phenomenon being studied (McMillan, 2000). Going to a social situation and
observing is a way of gathering information about the social setting (Denzin & Lincoln, 1994). In this study, the
researcher observed naturally occurring practices and class activities in regards to technology use in four
mathematics classrooms. Observation was completed in the participants’ classroom three times depending upon
their technology use in the classroom. An observation protocol was used in all observations in the participants’
classrooms. This observation protocol includes: the kind of technology used and for what purpose; whether
technology are placed in the hands of the students; and are students active or passive learners. Data collected
through this method was used to substantiate data collected in the interviews. Observations also helped identify any
gap that might exist between the data collected in the pre-interview and the data collected in the observation. If gaps
became apparent, post interviews were pursued with the respective participants.
Course Syllabus. Participant’s course syllabi were reviewed to give a better idea of the course content
taught by the participants. It was also used to examine how technology was adopted in the respective courses. These
syllabi were acquired from the participant’s webpage, emailed to me by the participants and/or given personally by
the participants during the first meeting.
Data Analysis
Data that surface from a qualitative design are termed emergent data (Charles, 1998; Merriam, 1998). The
processes of data collection and analysis are recursive and dynamic. Merriam (1998) stated that data that have been
analyzed while being collected should be both practical and revealing. Once a decision is made to end simultaneous
data collection and analysis, all of these information were brought together: interview logs or transcripts, field notes,
interview guides, and documents. The material should be organized so that data are easily retrievable (Merriam,
1998). Yin (2003) called this organized material the case study database. For this study, the database consisted of
interview logs or transcripts, field notes, and interview guides. They were referred to in the text and were also
included in appendices.
Several levels of analysis and interpretation are possible in case study research (Yin, 2003). The reader is
transported from simple descriptions of the phenomena under study to rich, thick description of the event (Stake,
1995). The case for each participant was analyzed by utilizing the transcription of each participant and read many
times to attempt to highlight the most important insights related to the focus of this research. In this regard, as
researcher, we acknowledge that in this process of presenting the findings we are “exercising judgment about what
is significant in the transcript” (Seidman, 2006, p. 118). What guided the researcher in doing this judgment of what
is important in the transcription are the research topic and the research questions. Data from the transcriptions were
compared with the research questions to identify the emerging categories. Once the emerging categories were
identified, data were coded based on the categories. For example, Dr. Grant discussed a technology tool adopted in
his class and how it is important for secondary mathematics pre-service teachers:
Dynamic geometry programs such as Sketchpad allow the creation of geometric objects such as lines and
circles so that their relationship to another screen object is established. This program can both change and
3
improve the teaching of geometry. The ability to explore geometric relationships with this program is
challenging without the use of technology.
This statement was coded as technology tools deemed important for secondary mathematics PSTs by the
participants.
Results & Analysis
From the data of the mathematics professors’ technology use in their respective classroom, three different
stages of technology adoption that these professors fall into were identified: “initial” user, “developing” user and
“engaging” user. These categorizations were based upon how technology was used in teaching mathematics courses.
The “initial user” category was for participants who adopt technology as a medium to accomplish calculations and to
deliver lectures. To some extent, technology was utilized to help create graphs, to help demonstrate or model
different mathematical situations; to supplement their lecture notes; and to help create a better visualization of
certain mathematical concepts. The “developing user” category was for participants who in addition to what the
“initial” user does with technology, creates examples using technology tools CAS or spreadsheets to give students
flexibility to manipulate attributes and visualize different mathematical occurrences. The “engaging user”
demonstrates a constructivist approach where students are encouraged to be active learners; the use of technology
tools was to facilitate this process where it involves student interaction with the content that allows knowledge
building and construction.
Dr. Hunt
Dr. Hunt is a Caucasian male professor who teaches numerical analysis, and has a teaching experience
more than 25 years in Higher Education. Dr. Hunt’s use of technology in the classroom was limited to a projector, a
computer and a program called Mathlab. Although, Dr. Hunt created static videos for his numerical analysis class,
these videos are merely for the students to refer to if they get lost with the class lecture. He also used a software that
comes with the textbook. He stated, “This software has a lot of examples that I can use in my class to illustrate some
of the numerical analysis concepts. It can also help the students in their understanding and they can at any time
access this software to look for more examples.” Class observations showed that he used the Mathlab program to
show examples. In one observation, he ran examples on sequence method using the Mathlab program. He also used
Logistic Map Applet to introduce the concept of nonlinear dynamics. Some of the homework assigned requires
students to use the Mathlab program and a Fortran program to solve it. In addition, Dr. Hunt also has a website
where students could access his course syllabi and the static videos he created using a screen capture program called
Camtasia.
Although technology was utilized in his Numerical Analysis classes, the use of technology was in doing
large calculations, graphing data, and demonstrates some numerical analysis concepts through examples. This was
evidence in the observations in his classes — technology such as the Internet, computer, overhead projector, and
Mathlab program was used three times only throughout the semester. Based on these data, I categorized Dr. Hunt as
an “initial user” of technology.
Dr. Grant
Dr. Grant is a Caucasian male professor who teaches Introduction to Higher Mathematics, and has a
teaching experience more than 17 years in the Higher Education. Dr. Grant articulated that the use of technology fits
well with his teaching philosophy especially in providing a platform for active learning. He explained, “I could
assign my students to do an investigation of how iterations of 100 times are solved. [In] Geometry class, [I use]
sketchpad. [It] helps discovering things and verifies them.” Dr. Grant’s use of technology in the class facilitated this
process where computer and Mathematica program required student interaction with the content and allows
knowledge building and construction. Dr. Grant stated: “Technology could help students discover things and help
verify these discoveries” and an excerpt from his class syllabus, “This is a very different course from courses like
pre-calculus calculus or differential equations, which are primarily focused on computations. Although there are
computations in this course, they are a tool for discovering, and proving, more general mathematical truths.” Dr.
Grant was the only participant that conducts his class in a computer lab, and each student had access to a computer
with the Mathematica program installed. Dr. Grant believed that technology could help students conceptualize
mathematics and empower them to explore practical applications of mathematics. His use of technology was to
support his pedagogy that Dr. Grant indicated focusing on active learning; pedagogy consistent with his beliefs that
mathematical knowledge was best learnt by investigating, exploring, and interacting with the content and with peers
to solve problems. It was easy for him to integrate technology in his class because the course itself is built around
technology. An excerpt from his course syllabus explained this statement, “Class time will be devoted exclusively to
4
labs. Each lab will start with a brief explanation of the question or problem to be explored. You will perform
experiments (usually with a computer or programmable calculator) and gather data. The data will lead you to make
your own conjectures, which you will then test and refine by further experimentation.”
Dr. Grant’s personal understanding of the role of technology and its advantages was vital to determine the
effectiveness of technology utilization in his classroom. Dr. Grant believed that technology as a tool can help
facilitate active learning environment and as a tool to reinforce or more efficiently deliver instructions. However, he
cautioned that one should make the effort to seize upon a technology opportunity when they perceive that it has
value and relevance to their work. For mathematics professors to use technology, they need to recognize the value
and relevance of technology for their students and their curriculum. Data gathered revealed that Dr. Grant is an
“engaging user” of technology in teaching his Introduction to Higher Mathematics course. Dr. Grant acted more as a
facilitator for the students’ construction of their own understandings rather than as a transmitter of concepts to them.
He accepted different ways that students did their problems and asked them to explain their reasons through
numerous experiments with the help of technology. The highly discursive nature of his classes, including his
insistence that students explain their answers, indicated that Dr. Grant believed that mathematical knowing has
social as well as cognitive aspects. As stated by Neo (2005), teachers and students must be able to make technology
function as a tool to engage them in mathematical activities, increase communication and facilitate collaboration.
Dr. Grant believed that technology could help students conceptualize mathematics and empower them to explore
practical applications of mathematics. He had been using technology to a significant degree in his classrooms and
had been viewed by the other three participants at South Mountain University as an enthusiast technology user.
Dr. Blum
Dr. Blum is a Caucasian male professor who teaches matrix algebra, and has a teaching experience more
than 20 years in the Higher Education. Dr. Blum communicated that technology could help students see illustrations
on some problems such as, using a java program is a good way for students to literally see some of the ideas
involved in linear equations such as to change the matrix A to a singular matrix. Dr. Blum is also one of the two
faculty members involved in a grant that requires him to implement homework modules in matrix algebra class. He
also created a matrix module using Geometer’s Sketchpad to help students to visualize 2x2 matrices. Dr. Blum
emphasized on students’ comprehension of the mathematical concepts, and to achieve this, it should be through his
strong presentation of the concepts. He believed that technology could aid in this process. He stated, “Technology
could facilitate students’ comprehension by allowing them to manipulate data and to proof and visualize occurrences
related to the concept on the various modules created using geometer’s sketchpad and Java programs.” However, Dr.
Blum argued that technology should not substitute the theoretical approaches of teaching. Lesson observations
showed that Dr. Blum’s use of technology was to support his pedagogy focusing on understanding the concepts, a
pedagogy consistent with his beliefs that mathematical knowledge was best learned by explanation and example.
Although he was involved directly with the grant that requires the use of homework modules in the Matrix Algebra
courses, he does not think that the modules support students’ understanding. He articulated, “Maybe it will help only
some because what we teach in this class is the computational aspect of matrix algebra; the modules help in
visualization but not in computational aspect. Full understanding still comes in understanding the theory. The theory
should be presented strongly.” Although, he was not convinced, just yet, that the use of the homework modules
could help in student understanding of the concepts taught in the matrix algebra class, he was not opposed to using
it. This could be due to the fact that this project grant is an ongoing project and he has not really studied the outcome
of using the homework modules. Dr. Blum articulated that using technology in his classes such as graphing
calculators could help ease tedious work, and with java modules it could help illustrate a 2x2 matrices. The whole
goal of using technology, he explained, was to support students’ comprehension of mathematics concepts and should
not be used to replace the core understanding of the concepts.
The data revealed that Dr. Blum is an “initial user”. He employed a predominantly transmission approach
to teaching, and modeled the use of technology in that process as scaffolding tools. For example, he used geometer’s
sketchpad to help students visualize the concepts of matrices ‒ linear transformation in 2-dimensions. His responses
indicated that he would encourage students to use technology to explore phenomena and to make sense of their
observations. This could help reinforce student’s understanding of the theory/abstract being taught. Dr. Blum
recognized that technology offered him and his students the opportunity to explore and model situations, tasks that
previously would have been very difficult for some student because of the long computational involved. Dr. Blum
appreciated the use of computers both as a calculational tool and as an aid to conceptualization.
Dr. Till
Dr. Till is a female professor who teaches matrix algebra and has a teaching experience more than 17 years
5
in the Higher Education. Dr. Till was involved in creating homework modules along with 4 other faculty members.
The homework modules were sent to the students through email; students’ learning from using these modules were
measured based on their effort of answering each question. Dr. Till indicated that she uses technology in her
teaching if it helps her students be active learners, and when its use provides different revelations of mathematical
concepts. She believed that technology could create an environment to show visualization and relationship amongst
concepts; and technology could also assist in tedious computational. She further stated, “Technology should be used
in a sense that students are encouraged in thinking about various aspects of concepts.” One example Dr. Till
mentioned was the use of Homework (HW) modules. These HW modules were used as another option to traditional
assignments. When using the HW modules, according to Dr. Till, students were exposed to different ideas of matrix
algebra before coming to the class. She believed that technology could be used as a catalyst for students to think
about other aspects of the concepts being taught. She stated, “For example, the Mathematica program is almost like
a virtual laboratory where it allows students to explore various aspect of matrix algebra.” Lesson observations
showed the use of a projector, transparencies and calculators as tools to transmit mathematical knowledge and to do
calculations. Data from the interviews and lesson observations indicated that Dr. Till’s use of technology was
limited to doing calculation and as a visualization aid. Based on the data I categorized Dr. Till is an “initial user”.
She saw the role of technology as demonstrating mathematics concepts, graphing and visualizing data, and doing
large calculations. Although, she indicated that modeling the use of technology in a meaningful and constructive
ways would benefit secondary level pre-service mathematics teachers, there was no evidence in her classroom to
support this sentiment.
Table 3 summarized the stages of technology adoption by each participant, how technology was used in the
classroom and the type of technology tools adopted in the classroom.
Table 3: Summary of Technology Adoption
Category
Stage of
Technology
Adoption
Dr. Hunt
“Initial’
Dr. Grant
“Engaging”
Dr. Blum
“Initial”
Dr. Till
“Initial
How technology
was used
Supplement to class
lecture (Static
video); Calculation;
Illustration
Experimentation;
Calculation;
Graphing;
Demonstration
Visualization;
Calculation;
Manipulation;
Graphing
Visualization;
Computation
Type of
technology used
Camt; Mathlab;
Fortran
Mathematica;
World Wide Web;
Sketchpad;
Calculator
Geometer sketchpad;
Graphing calculators
Blackboard;
Computer Algebra
System;
Conclusion and Implications
This study focused on technology adoption by mathematic professors. The three stages in which university
faculty moves in the technology adoption process suggested by Celsi and Wolfinbarger (2002) was used to
determine the mathematics professors category of technology adoption. Results indicated that out of four
mathematics professors, three of them demonstrated as “initial” users of technology ‒ Dr. Hunt, Dr. Blum and Dr.
Till. The use of technology was modeled to accomplish calculations and to deliver lectures. To some extent,
technology was utilized to help create graphs, to help demonstrate or model different mathematical situations; to
supplement their lecture notes; and to help create a better visualization of certain mathematical concepts. A more
“engaged” or constructivist approach was demonstrated by Dr. Grant where he encouraged his students to be active
learners. He modeled the use of technology in the lab to facilitate active learning where the technology (computer
and Mathematica program) involves student interaction with the content that allows knowledge building and
construction. Students are encouraged to work in pairs, to discuss freely on the outcomes of the problems, and to
explore other possible solutions using the Mathematica program. The way technology was adopted in Dr. Grant’s
classroom was to supports active and constructive learning, and I categorized him as an “engaging” user of
technology. The findings suggest that to adopt technology into their instruction in innovative ways, mathematics
professors may have to reconsider their pedagogical beliefs. However, requiring mathematics professors to change
6
their pedagogical beliefs can be a daunting task because it may involve challenging fundamental beliefs. There is
also a need to encourage mathematics professors to develop a teaching philosophy that includes technology adoption
and modeling the use of technology. For successful technology integration in schools, mathematics professors who
are intimately involved in preparing future K-12 mathematics teachers play a crucial role. Since the Department of
Mathematics is typically a separate entity from the College of Education, it could be difficult for the College of
Education to have an impact on the teaching modeled by faculty from other departments. Both parties could work
together in providing engaging or constructivist learning environment for teacher preparation on technologies. As
mentioned above, research shows that teachers tend to teach the way they were taught. Therefore, if we expect preservice secondary mathematics teachers to teach in a constructivist or engaging way using technology, professors
need to be teaching them in constructivist or engaging ways using technology. These professors should structure the
learning environment so that they will have the opportunity to model expert behavior to students in sound uses of
technology-based teaching and learning. It is important that these professors are skilled in technology-based learning
because only then they can model to their pre-service secondary mathematics teachers’ expert behavior.
Mathematics professors should demonstrate effective use of technology in their teaching and by modeling
appropriate technology tools in teaching and learning mathematics concept.
This study concluded that three out of four of the mathematics professors are not using technology in an
engaging way for students learning mathematics, although they indicated that they are familiar with some
technology tools. There is much more to using technology and modeling its use effectively in a classroom than
simply being more familiar with the tools. Further research is needed to explore how to help these mathematics
professors progress from “initial” users to “developing” users and, ultimately, as “engaging” users of technology and
modeled its use appropriately to future in-service mathematics teachers. Since mathematics professors are already
familiar with technology basics, there is more to examine about what is needed to help these mathematics professors
to use these skills effectively in teaching mathematics concepts.
Reference
Artigue, M. (2002). Learning mathematics in a CAS environment. The genesis of a reflection about instrumentation
and the dialectics between technical and conceptual work. International Journal of Computers for
Mathematical Learning, 7(3), 245-274.
Bitner, N., & Bitner, J. (2002) Integrating technology into the classroom: Eight keys to success. Journal of
Technology and Teacher Education, 10, 95-100.
Celsi, R. & Wolfinbarger, M. (2002). “Discontinuous Classroom Innovation: Waves of Change for Marketing
Education”. Journal of Marketing Education, 24 (1), 64-72.
Charles, C. M. (1998). Introduction to educational research. White Plains, NY: Longman.
Creswell, J. (1998). Qualitative Inquiry and Research Design: Choosing Among Five Traditions. California, CA:
SAGE Publications.
Denzin, N. K., & Lincoln, Y. S. (1994). Handbook of qualitative research (Eds.). Thousand Oaks, CA: SAGE
Publications.
Hagenson, L. (2001). The integration of technology into teaching by university college of education faculty.
Unpublished master’s thesis, Oklahoma State University, Stillwater, OK.
Heid, M. K. (1997). The technological revolution and the reform of school mathematics. American Journal of
Education, 106, 5-61.
Johnson-Gentile, K., Lonberger, R., Parana, J., & West, A. (2000). Preparing preservice teachers for the
technological classroom: A school-college partnership. Journal of Technology and Teacher Education,
8(2), 97-109.
Jonassen, D. H., Howland, J., Moore, J. & Marra, R. M. (2003). Learning to solve problems with technology: A
constructivist perspective. New Jersey: Pearson Merrill Prentice Hall.
7
Lavicza, Z. (2006). The examination of Computer Algebra Systems (CAS) integration into university-level
mathematics teaching. Retrieved Dec 10, 2010, from
http://elib.lhu.edu.vn/bitstream/123456789/4867/1/c33.pdf
Lavicza, Z. (2008a). Factors influencing the integration of computer algebra systems into university-level
mathematics education. Journal of Technology in Mathematics Education, 14(3), 121-129.
Leatham, K. (2007). Pre-service secondary mathematics teachers’ beliefs about the nature of technology in the
classroom. Canadian Journal of Science,Mathematics and Technology Education, 7(2/3), 183-207.
Mathematics Association of America (1991). A call for change: Recommendations for the preparation of teachers of
mathematics. Washington, DC: Author.
Mathematical Sciences Education Board (1991). Counting on you: Actions supporting mathematics teaching
standards, Washington, DC: Author.
McMillan, J. H. (2000). Educational research: Fundamentals for the consumer. New York, NY: Longman.
Merriam, S. B. (1998). Qualitative research and case study applications in education. San Francisco, CA: JosseyBass Publishers.
Merriam, S. B. (2002a). “Assessing and Evaluating Qualitative Research.” In Qualitative Research in Practice:
Examples for Discussion and Analysis, edited by S. B. Merriam, pp. 18-33. San Francisco: Jossey-Bassa.
National Council of Teachers of Mathematics (2000). Executive Summary: Principles and standards for school
mathematics. Reston, VA: Author.
Neo, M. (2005). Web-enhanced learning: Engaging students in constructivist learning. Emerald Insight, 22(1), 4-14.
Retrieved April 4, 2007, from Emerald database
Patton, M. Q. (1990). Qualitative evaluation and research methods (2nd Ed.). Newbury Park, CA: Sage
Publications.
Pierce, R. L., & Stacey, K. (2004). A framework for monitoring progress and planning teaching towards the
effective use of Computer Algebra Systems. International Journal of Computers for Mathematical
Learning, 9(1), 59-93.
Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). New York: Free Press.
Seidman, I. (2006). Interviewing as qualitative research: A guide for researchers in education and the social
sciences. New York, NY: Teachers College Press.
Sherry, L. (1997). The Boulder Valley internet project: Lessons learned. T.H.E. Journal (Technological Horizons in
Education), 25(2), 68-73.
Sherry, L., Tavalin, F., & Gibson, D. (2000). New insights on technology adoption in schools. T.H.E. Journal
(Technological Horizons in Education), 27(7), 42-48.
Sherry, L., & Gibson, D. (2002). The path to teacher leadership in educational technology. Contemporary Issues in
Technology and Teacher Education [Online serial], 2(2).
Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: SAGE Publications.
Yin, R. K. (2003). Case study research: Design and methods. (3rd Ed.). Thousand Oaks, CA: Sage Publications.
8