Descriptive Indicators of Future Teachers’ Technology Integration in the PK-12 Classroom: Trends from a Laptop-Infused Teacher Education Program

DESCRIPTIVE INDICATORS OF FUTURE TEACHERS’ TECHNOLOGY
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Descriptive Indicators of Future Teachers’ Technology Integration in the PK-12 Classroom:
Trends from a Laptop-Infused Teacher Education Program

Joan E. Hughes
The University of Texas at Austin
Curriculum and Instruction Department
1912 Speedway STOP D5700
Austin TX 78712-1293 USA
Phone: 512.232.4145; Fax: 512.471.8460
Email: joanh@austin.utexas.edu
Acknowledgment
The author graciously acknowledges and thanks Yu-Chi (Nikki) Wen for her participation in
data preparation and analysis.
Abstract
This research examined preservice teacher graduates’ positioning towards integrating technology
in future teaching. Participants included 115 preservice teachers across three cohorts in 20082009 who graduated from a laptop-infused teacher education program. The study implemented a
case study methodology that included a survey administered upon graduation. Indicators of
positioning towards technology integration included: digital technology self-efficacy, attitude
toward learning technologies, pedagogical perspective; personal/educational digital technology
behaviors during the program; and TPACK knowledge used to rationalize their most valued
technologies for future teaching. Results indicated graduates held moderate digital technology
self-efficacy, positive attitude toward learning technologies, and moderate constructivist
philosophy. During their preparation, productivity software activities were used most widely for
educational purposes. Their most valued technologies for teaching subject matter were
predominantly productivity software as well as general hardware, such as computers, projectors,
and document cameras. They described teacher-centric uses 3 times more often than studentcentered. Graduates showed low depth of TPACK. Teacher education programs need to consider
the degree to which their candidates are exposed to a range of contemporary ICTs, especially
content-specific ICTs, and the candidates’ development of TPACK, which supports future

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technology-related instructional decision-making. Such knowledge is developed across the
teaching career, and technological induction programs may support continued TPACK
development. Future research should employ longitudinal studies to understand TPACK
development and use across novice and veteran teachers.

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Descriptive Indicators of Future Teachers’ Technology Integration in the PK-12 Classroom:
Trends from a Laptop-Infused Teacher Education Program
Involving mobile technologies, such as laptops, within professional teacher preparation
moves the discipline away from the one-course technology skills approach, which can be
isolationist and lack content connections (Friedman & Kajder, 2006; Kay, 2006a; Lipscomb &
Doppen, 2004/2005; Polly & Shepherd, 2007; Wang, 2002), to an ongoing, integrated learning
approach that infuses technology across the curriculum, including content and methods
coursework, field experiences, and student teaching. This integrated approach affords mobile
computing ubiquity and subject-specific use during preparation, may scaffold development of
preservice teachers’ knowledge, understanding, and dispositions of technology integration in PK12 learning (e.g., Clift, Mullen, Levin, & Larson, 2001), and may reduce obstacles that prevent
technology integration, such as lack of time, teaching philosophy, education faculty’s
technological skills, technological problems, and insufficient access (Kay, 2006a). Very few
teacher education programs have adopted laptop requirements across certification areas and
preparatory experiences, such as described by Meyers (2006), Tothero (2005), and in research by
MacKinnon, Aylward, and Bellefontaine (2006). Thompson, Schmidt, and Davis (2003) describe
a K-6 program renewal involving laptops but indicate involvement of two preservice cohorts,
about 45 students. Laptops have been introduced programmatically to specific certification areas,

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such as special education (Allsopp, McHatton, & Cranston-Gingras, 2009) or STEM (Kay,
2006b; 2007a; 2007b) or only to the education faculty (Savery & Reed, 2006).
Empirical research from the few laptop/mobile-intensive programs indicates preservice
teachers’ increased perceptions of their abilities to integrate technology into teaching and
consistent high attitudes towards integration (Allsopp et al., 2009), gender equalization in
computer attitudes and computer ability by graduation (Kay, 2006b), increased positive emotions
and reduced negative emotions correlated with computer use at the university and student-use
and teacher-use in the field (Kay, 2007a), and a preference for authentic tasks and collaborative
strategies predicting teacher use of computers (Kay, 2007b).
This research study was situated in a preservice teacher education program with
ubiquitous mobile laptop computing. It examined preservice teacher graduates’ positioning in
terms of key concepts that influence future technology integration: digital technology selfefficacy, attitude towards learning technologies, pedagogical perspective, and most-valued
content area technologies for future teaching. Based on the literature, these key concepts
influence future choices regarding technology integration within content area teaching.
Research Questions
The research question guiding the inquiry was: To what degree are graduates of a laptopinfused teacher preparation program prepared to integrate technology in their future classrooms?

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Several indicators, such as graduates’ self-reported beliefs, attitudes, behaviors, and knowledge,
framed the sub-questions:
•

What levels of digital technology self-efficacy, attitude toward learning technologies, and
constructivist pedagogical perspective do preservice teacher graduates possess?

•

What were preservice teachers’ personal and educational digital technology behaviors
during the program?

•

What digital technologies do preservice teacher graduates most value for future contentspecific teaching and learning, and how do they use their knowledge to rationalize their
choice(s)?
This research focused on a moment-in-time, specifically the transitional moment from

preservice to certified teacher. Learning to use innovative technologies to positively influence
teaching and learning also necessitates learning across the career (Borko, Whitcomb, & Liston
2009), which represents another important but broader research topic.
Conceptual Frames
I conceptualize “technology integration” as the use of digital information communication
technologies (ICT) by teachers and/or students that support constructivist and socioconstructivist instruction and learning (Cole, 1996; Greeno, 1989; Greeno, Collins, & Resnick,
1996; Vygotsky, 1978) of subject area content (e.g., math, science, social sciences, languages,

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etc.). Optimal learning, from this perspective, is a social practice that involves individual or
group participation in activities that make use of contextually- and culturally-relevant (i.e.,
global, community, cultural, and individual) artifacts across time and spaces. Similar to the role
of technology within contemporary standards (e.g., Common Core, 2010a; 2010b; Jenkins,
2006), ICT integration occurs when it extends content area learning. The Common Core (2010a)
depicts students “employ[ing] technology thoughtfully,” “efficiently,” and understanding
technology’s “strengths and limitations” (p. 7). ICT is adopted when it strategically adds value to
content area learning, not as a content topic itself (Porter, McMaken, Hwang, & Yang, 2011).
Content-based technology integration occurs as teachers employ their knowledge, beliefs, and
pedagogy to choose particular ICT adoptions to support content learning (Fullan, 2007; Zhao,
Pugh, Sheldon, & Byers, 2002). As new teachers enter their classrooms, they face many
decisions concerning the use, purposes, availability, and capabilities of ICT for
teaching/learning.
Instructional Decision Making
In a learning context in which ICT is situated within all the preservice learning
experiences, such as university courses, fieldwork, and student teaching, preservice teachers may
establish more developed knowledge and experience of how ICT informs their pedagogy and
content area curriculum. Novice teachers will draw on this personal knowledge and experience

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with ICT, along with information about their classroom and school, to plan how to use
technology as novice teachers (Carter, 1990). In preparing teachers to integrate ICT for teaching
and learning, certain characteristics or program experiences may more likely lead to future
technology integration in the classroom. Teachers who are self-efficacious towards digital
technologies (Anderson, Groulx, & Maninger, 2011; Cassidy & Eachus, 2002; Chen, 2010; Sang,
Valcke, van Braak, & Tondeur, 2010), have positive attitudes toward the use of learning
technologies in education (Anderson et al., 2011; Anderson & Maninger, 2007; Brinkerhoff,
2006; Cullen & Greene, 2011; Sang et al., 2010), and possess more constructivist philosophy and
pedagogy (Ravitz, Becker, & Wong, 2000; Overbay, Patterson, Vasu, & Grable, 2010; Sang et
al., 2010) are more likely to consider using technologies in teaching (Chen, 2010; Ertmer &
Ottenbreit-Leftwich, 2010; Sang et al., 2010). Therefore, in this study, I was particularly
interested in preservice teachers’ technological self-efficacy, attitude toward the integration of
ICT in teaching and learning, and current pedagogical perspective as they graduate and are
poised to become new teachers.
Self-Efficacy, Attitude, and Pedagogical Perspective
Self-efficacy is a belief in one’s capability to accomplish a task (Bandura, 1977) and
digital technology self-efficacy measures individual self-efficacy beliefs regarding computer and
ICT-related tasks. In a study of 25 exemplary technology-using teachers, Ertmer, Ottenbreit-

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Leftwich, and York (2007) found that teachers with higher self-efficacy were more likely to
overcome barriers to technology integration. Some consider ‘attitude’ as a predictor variable,
such as Anderson and Maninger (2007), who discovered a positive relationship between
preservice teachers’ attitude about technology integration and their potential use of technology in
their future classrooms. Ravitz, Becker, and Wong (2000) found that constructivist-oriented
teachers tended to have higher Internet use and value the Internet more compared with teachers
with traditional pedagogy. Overbay et al.’s (2010) recent study with 474 North Carolina teachers
discovered that teachers’ beliefs about technology as a constructivist teaching tool were
significant predictors of teacher technology use. Therefore, in this research, I aimed to
understand preservice teachers’ digital technology self-efficacy, attitudes towards learning
technologies, and current pedagogical perspective at their moment of degree completion and
teacher certification.
Technological Pedagogical Content Knowledge
I employed the conceptual frame, Technology Pedagogical Content Knowledge (TPCK
or TPACK) (Angeli & Valanides, 2005; 2009; Cox & Graham, 2009; Hughes, 2005; MargerumLeys & Marx, 2002; Mishra & Koehler, 2006; Mouza & Wong, 2009; Niess, 2011), which
clarifies what knowledge teachers develop as they learn about the use of digital technologies
within educational settings. While definitions of the model’s constructs (i.e., CK, PK, PCK, TK,

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TCK) have considerable variation and “fuzzy” boundaries (Angeli & Valanides, 2009; Cox &
Graham, 2009; Graham, 2011; Jimoyiannis, 2010), I possess a transformative view (Graham,
2011; Mouza & Wong, 2009) that each of these constructs is distinct, but that integrated
together, they form the construct of TPACK. When teachers begin to consider how digital ICT
plays a role in teaching a content-related concept and students’ learning about content, they are
developing TPACK. Teachers ultimately draw upon TPACK to guide their choices of how to
involve ICT in teaching and learning. Research of preservice education that conceptually employ
TPACK (e.g., Cavin & Fernandez, 2007; Koh & Divaharan, 2011; Niess, 2005; Ozgun-Koca,
Meagher, & Edwards, 2010; Schmidt et al., 2009) highlight the importance of experiences and/or
modeling of content-specific, technology-supported lessons to develop preservice teachers’
TPACK, which, in turn, helps learners of content transition into teachers of content. Employing a
TPACK framework in this research study offers insight into how preservice teacher graduates’
current knowledge may inform their future instructional decisions, as represented in a choice of
their most-valued technologies.
These conceptual frames–digital technology self-efficacy, learning technology attitudes,
pedagogical positioning, and TPACK–outline the research-based indicators of future classroom
technology use and enable an understanding of graduates’ dispositions that research has shown
influences future decision-making and technology-supported pedagogy.

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Method
Research Design
This research employed a descriptive case study methodology to provide insight into the
case of technology-rich preservice teacher preparation, a type of instrumental case (Stake, 1995).
The sampling was purposeful and guided by a theoretical/operational construct (Patton, 2002),
specifically –a preservice program that had established ubiquitous mobile laptop integration by
students and teachers across the program. Thus, the case is one teacher preparation program.
Research Context
This research occurred within one teacher education program at a large U.S. university.
With support of its faculty and administration, in 2002 the program created a ubiquitous laptop
environment designed to immerse preservice teachers in technology-rich learning environment
with ample tools, Internet access, support, and learning/content management systems. All
preservice teacher certification programs, with the exception of secondary science and math1,
required students to purchase a Macintosh laptop.
During the first few years, extensive effort focused on integrating technology into the
curriculum through technology training workdays in which faculty developed lesson plans,

1
A requirement was not instituted because cross-platform technological practices were already
in use, and data indicated most faculty and students already owned a laptop.

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technology-enriched assignments, and assessment rubrics. Such work allowed faculty to
integrate and model technology within their content expertise areas. In the last five years, faculty
support became individually-focused, on-demand, and/or ongoing through a professionallystaffed center for instructional design and ICT integration. All faculty are required to incorporate
technology into university courses. Examples of technology integration within preservice teacher
education courses include: development of multimedia lessons, newsletters, and presentations;
exploration of subject-specific software; use of databases, spreadsheets, simulation software,
VoiceThreads, ComicLife, class management systems, such as BlackBoard, and online
discussions; designing webpages; classroom reflections blog or course blog; video-reflection of
self-teaching; iMovie projects; exploration of webquests, Inspiration, United Streaming, and
iPhoto.
New students attend a half-day technology orientation for preliminary introduction to
their computer, operating system, applications, and college and university resources. Students
may attend optional workshops about using their laptop as a learning tool, and faculty may
organize within-class workshops as needed to support specific content and project needs. Faculty
and students have access to Atomic Learning online software tutorials. A college-level
technology center provides workshops, a student-staffed help desk for student software/hardware
support, technology check-out, technology-enhanced meeting areas or classrooms, high-end

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computers for media production, and high-speed wireless Internet.
Participants
Enrolled students in this U.S. university preservice teacher education program
participated in this research. Students who participated included graduates from three preservice
cohorts who voluntarily consented according to IRB-approved research protocols in: Fall 2008 (n
= 42), Spring 2009 (n = 53), and Fall 2009 (n = 20). Participants were certified in a range of
programs, including: Early Childhood through 6th Grade (n = 64), Kinesiology (n = 8), Special
Education (n = 2), Middle/Secondary English (n = 18), Middle/Secondary Languages Other
Than English (n = 5), Middle/Secondary Social Studies (n = 12), and All-level Fine Arts,
including Art, Music and Theater (n = 6).
Data Sources
Data include a 20-30 minute end-of-program survey. The survey items used in this
research include:
•

A 17-item digital technology self-efficacy measure adapted from Holcomb, King, &
Brown (2004) who reported reliability ∝=0.80. Language was updated replacing
computer with digital technology. Items were measured with a scale of 1 (strongly
disagree) to 4 (strongly agree). A 1.0 score reflects low digital technology self-efficacy,
while a 4.0 represents high digital technology self-efficacy.

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A 12-item attitude toward learning technologies measure, from the “Technology Beliefs”
section of Brinkerhoff (2006) who reported reliability of
∝=0.69. Items were measured
on a scale of 1 (strongly disagree) to 4 (strongly agree). A measure of 1.0 reflects a
negative perspective while a 4.0 represents a positive outlook on utilizing learning
technologies in the classroom.

•

A modified 10-item version of Becker and Anderson’s (1998) pedagogical perspective
measure. The 10 items were measured on a scale of 1 (strongly disagree) to 4 (strongly
agree). A measure of 1.0 reflects a preference for direct instruction while a 4.0 reflects a
more constructivist orientation.

•

Use, frequency, purpose (personal/educational), and skill level of Technology Activities
during the preservice program in the following themes: (a) communication (12 items), (b)
web (eight items), (c) productivity (six items), (d) creation (seven items), and (e) and
education-specific software/hardware (three items). Items were adapted from ECAR 2008
survey (Students, 2008). Frequency of use was measured on a 4-point scale from monthly
or less, weekly, daily, or many times per day. Purpose was measured on a 7-point scale
from 1 (All Personal Use) to 7 (All Educational Use) with a 4.0 representing equal use
for personal and educational. Skill was measured on a 5-point scale including: 1 (not at
all skilled), 2 (not very skilled), 3 (fairly skilled), 4 (very skilled), to 5 (expert).

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Two open-ended questions about future uses of technology and content-connections:
o Q1: “Describe the most valuable learning technology (a technology you could not
imagine teaching without) that you or your students will use in the future, if
available.”
o Q2: “Please explain why your chosen learning technology (listed above) is so
valuable, such as its value to you and your students, how you or your students will
use it, and what objectives it helps you reach.”
Consenting participants were emailed an invitation to complete the online survey two

weeks prior to graduation. Three email reminders across two weeks were sent before the survey
closed.
Data Analysis
Descriptive statistics were calculated for survey items within SPSS. Scale scores (digital
technology self-efficacy, attitude toward learning technologies, and pedagogical perspective)
were calculated and reliability established for the participant pool. Internal reliability, as
measured by Cronbach’s alpha, was good (above .7) or high (above .8) for the three scales (see
Table 1). This means the three scales each measure a single construct.
Table 1
Reliability of Scales by Graduate Cohort

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Scale

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Fall 2008

Spring 2009

Fall 2009

(n=42)

(n=53)

(n=20)

Cronbach’s Alpha
Digital Technology Self-Efficacy (17

.960

.956

.956

.849

.880

.730

.786

.750

.812

items)
Attitude toward Learning Technologies
(12 items)
Disposition toward Constructivism (10
items)
We2 engaged in qualitative analysis procedures regarding analysis of two open-ended
questions in the survey. The data from these questions were analyzed in several ways. First, we
counted how many learning technologies each respondent mentioned in the answer to Q1.
Second, we coded the answers to Q1 and Q2 for the explanatory ideas and the knowledge that
such explanations represented using an a priori TPACK codebook generated from earlier studies
(Hughes, 2005; Mouza & Wong, 2009) (see Appendix for codebook). We collaboratively coded
Q1 and Q2 to assure 100% agreement. We identified explanatory chunks. In some cases, an
explanatory chunk would be an entire sentence; in other cases, it was a phrase within a sentence.
We coded each explanatory chunk for the TPACK code (see Appendix) that best represented the

2
See Acknowledgments.

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meaning of the chunk. We chose the knowledge type that represented the chunk’s essence rather
than assigning codes that represents parts of the chunk’s essence. For example, if the respondent
wrote about using the technology because it motivates children, this was coded as TPK (rather
than TK + PK) because the writer presents the reasoning as an integrated idea. Likewise, if a
respondent discusses how it is difficult for learners to read Shakespeare texts because these texts
are meant to be performed, not read, this explanatory idea was coded as PCK (rather than
CK+PK) because the writer presents the reasoning as an integrated idea rather than separate
ideas. The value of the TPACK framework is to understand the degree to which teachers are
integrating their knowledge, so we were more interested capturing integrated ideas through our
coding than breaking integrated ideas down into individual concepts.
Next, we coded the frequency and type (student vs. teacher) of technology uses described
in these preservice teachers’ LT choice and/or rationale for their future PK-12 students. For
example, when a respondent described a teacher using PowerPoint to show pictures or
information, such a use was coded as a teacher use. Student uses were situations in which
students would physically manipulate a technology. For example, when a respondent described
students researching on the Internet, such a response was coded as a Student Use. In rare cases,
the respondent would describe a use that potentially involved both teachers and students, such as
using MS Word “to help students publish work;” in such cases we coded that use as both teacher

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and student use. All codes were quantified and disaggregated by graduate cohort for display.
Results
The research aimed to understand how the graduates of this teacher preparation program
were prepared to integrate technology in their future classrooms, as represented by several
indicators at their graduation and formal certification. Results are reported by each research
question.
Preservice Teachers’ Digital Self-Efficacy, Learning Technology Attitude, and Pedagogical
Philosophy
All three cohorts completed their program with moderate digital technology self-efficacy.
Fall 2009 cohort had the highest mean score of 3.15 (n = 19, variance = 0.29, SD = 0.54),
followed by fall 2008 cohort with a mean score of 3.08 (n = 37, variance = 0.31, SD =0.55), and
spring 2009 graduates had slightly lower mean score of 3.06 (n = 48, variance = 0.27, SD = 0.52).
The participants held moderate confidence in using digital technologies for general purposes.
The preservice graduates reported working with digital technology to be easy, had sufficient
abilities to use digital technology, and did not experience many problems when trying to use
digital technology.
In relation to learning technologies, defined as digital tools put to use for teaching and
learning purposes, all three cohorts reported strong positive dispositions towards the use of

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learning technologies in classroom instruction. Fall 2008 graduates’ mean score, 3.32 (n = 40,
variance = 0.153, SD = 0.39), spring 2009 graduates’ mean score of 3.20 (n = 48, variance =
0.155, SD = 0.39), and fall 2009 graduates’ mean score of 3.35(n = 18, variance = 0.091, SD =
0.30) were all high. The high mean scores in their attitudes toward learning technologies
revealed that preservice graduates perceived more affordances than constraints for learning
technologies to support teaching and learning.
All three cohorts reported moderate constructivist beliefs with fall 2008 graduates
reporting a mean score of 2.93 (n= 32, variance = 0.147, SD = 0.38), spring 2009 cohort with a
mean score of 3.04 (n = 37, variance = 0.113, SD = 0.34), and Fall 2009 cohort reporting the
highest mean score of 3.09 (n =17, variance = 0.156, SD = 0.39). Participants generally place
value on student-centered learning and teaching, including an active role for learners. Their mean
scores reflect that these preservice graduates also indicated some preference toward direct
instruction in their teaching.
In summary, these graduates appear to be moderately positioned in terms of their selfefficacy, attitudes, and philosophy. The literature has established that more positive scores on
these indicators increase the possibility for technology integration in future teaching.
Preservice Teachers’ Personal and Educational Digital Technology Behaviors During
Preparation

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As Kay (2006a) noted, it is imperative to understand preservice teachers’ technology use.
The extent to which technologies are used during the program generates new teachers’
technological experience base. Several distinctive patterns exist in the preservice teachers’
technological activities (see Table 2). First, most (between 52-71%) preservice teachers reported
using technologies for education-specific, communication, or productivity activities. Second,
preservice teachers used communication technologies most often, almost daily, and used web
activities weekly. Third, the only technologies put to use more for educational purposes were
productivity activities while all the other technologies were more used more for personal
purposes. Fourth, preservice teachers perceived similarly high skill across all technology
activities. Overall, these preservice teachers primarily used word processing, Internet browsing,
and presentation (e.g., Powerpoint/Keynote) for educational purposes almost weekly.

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Table 2
Participants’ Reported Technology Usage and Skill Level
Participants

Participants’

Type of

Skill

reporting use

frequency of use1

usage2

level3

during program

(mean)

Communication activities (e.g., email, blog, wiki,

Fall 08

52%

2.59

3.29

3.82

instant messaging, discussion board and online

Spring 09

64%

2.60

3.16

3.89

audio/video interactions)

Fall 09

68%

2.39

3.24

3.79

Total

60%

2.55

3.22

3.85

Web activities (e.g., podcasts, online videos, social

Fall 08

43%

1.89

2.31

3.78

networking sites, online multiuser computer games,

Spring 09

46%

2.24

2.74

4.00

online virtual worlds, and social bookmarks)

Fall 09

50%

2.39

3.05

3.61

Total

46%

2.14

2.64

3.85

Productivity activities (e.g., word processing,

Fall 08

54%

1.88

5.48

3.80

spreadsheets, presentation software, concept maps and

Spring 09

52%

1.87

5.66

3.69

desktop publishing)

Fall 09

49%

1.90

5.70

3.78

DESCRIPTIVE INDICATORS OF FUTURE TEACHERS’ TECHNOLOGY INTEGRATION

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Total

52%

1.88

5.60

3.74

Creation activities (e.g., digital arts/audio/video,

Fall 08

36%

1.34

3.13

3.49

webcasts, photo galleries and web pages)

Spring 09

41%

1.26

4.09

3.39

Fall 09

36%

1.40

4.09

3.39

Total

38%

1.32

3.74

3.42

Education specific technologies (e.g. E-portfolios,

Fall 08

68%

1.78

N/A

3.38

course management systems and subject-specific

Spring 09

72%

2.04

N/A

3.45

software)

Fall 09

76%

1.92

N/A

3.29

Total

71%

1.93

N/A

3.40

Note: 1Reported on a scale of 1 (Monthly or less), 2 (Weekly), 3 (Daily) to 4 (Many times per day)
2

Reported on a scale of 1 (All personal use), to 4 (Uses equally for personal and educational use) to 7 (All educational use)

3

Reported on a scale of 1 (Not at all skilled) to 5 (Expert).

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Preservice Teachers’ ‘Most Valued’ Digital Technologies and Use of TPCK in Rationales
We conducted several examinations of the preservice graduates’ responses generated
from “what is the most valuable learning technology that you cannot imagine teaching without
that you or your students will use in the future, if available?” Each participant across all cohorts
generated a mean of 1.6 learning technology items (see Table 3). Preservice graduates seem to
most value productivity software, such as PowerPoint and Word, as well as general hardware,
such as computers, projectors, and document cameras (e.g., Elmo). There were few contentspecific learning technologies mentioned: Word and iMovie (related to English Language Arts
writing process activities and publishing), math/reading games, digital audio creation (for fine
arts/music), and theater performance videos on YouTube.
Table 3
Type and Frequency of Learning Technologies Identified
Graduate Cohorts
Type of Learning

Fall 2008*

Spring 2009*

Fall 2009*

Total

Technologies

(Frequency

(Frequency

(Frequency

Cited)

Cited)

Cited)

PowerPoint, Keynote

12

8

5

25

Computer, laptop

7

7

2

16

Internet access, The web

4

7

4

15

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Computer Projector

6

3

3

12

Document Camera,

2

3

3

8

3

4

1

8

MS Word

1

6

iMovie

2

2

2

6

Smart Board/Promethean

1

1

2

4

3

1

4

ELMO
YouTube, Online Videos,
United Streaming
7

Whiteboard
Movie clips, Videos (not
online)
Kidspiration, Inspiration

1

Email

3

3

Music

2

3

2

2

iPhoto, Images

1

iTunes

1

Stereo with input (CD,

1

2
1

1

1

1

1

iPod)
MS Excel
Digital audio creation

1

1

1

1

system
Blackboard
Math or Reading games

1

1

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Weblog
Total LTs, Mean, SD

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1
43, 1.6, 0.80

53, 1.5, 0.98

1

26, 1.6, 0.81

121

*Note: n=27; n=35; n=16, respectively.
We also examined the extent to which these learning technologies were used by teachers
and/or students. In fall 2008, 12 student uses (M = 0.44; SD = 0.64) and 36 teacher uses (M =
1.33; SD = 1.39) were described; in spring 2009, 16 student uses (M = 0.46; SD = 0.82) and 41
teacher uses (M = 1.17; SD = 1.01) were described; in fall 2009, 7 student uses (M = 0.44; SD =
0.63) and 14 teacher uses (M = 0.88; SD = 0.81) were described. The three graduate cohorts all
identified 2 or 3 times as many teacher uses of learning technologies than student uses, which
may dispose these graduates to use more teacher-centric technologies when they become novice
teachers.
Finally, we examined how their written rationales for choosing valuable learning
technologies represented types of knowledge that teachers use in pedagogical decision-making.
Conceptually, we argue that a preservice graduate’s rationale reflects more depth when it
contains a range of knowledge types (e.g., TCK, TPK, CK). To gauge the depth of reasoning, we
examined the number of explanatory ideas present (number of blocks on x-axis) as well as the
type(s) of knowledge associated with each idea (color coded blocks) (see Figures 1, 2, and 3).
These visualizations are an approximation of the TPACK employed to rationalize their choices,

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as it shows both the number and type of TPACK-coded explanatory ideas. On average, a
respondent provided two explanatory ideas to rationalize their valuable learning technology
choices (Fall 2008: 50 explanatory ideas (M = 1.9; SD = 1.23); Spring 2009: 63 explanatory
ideas (M = 1.8; SD = 1.05); Fall 2009: 32 explanatory ideas (M = 2; SD = 1.21)). Preservice
graduates relied mostly on technological pedagogical knowledge (TPK, the blue bar) to justify
why they determine certain technologies to be most valuable for their future. The frequency of
TPK may indicate that preservice graduates have more knowledge regarding how technology
may be used for general pedagogical purposes. TPK is a broad category of knowledge (see
Appendix for coding categories) that captures ideas related to instruction, assessment, classroom
management, National Educational Technology Standards (NETS), and lesson planning. The
most frequently cited TPK evidence included use for general pedagogical tasks (#6 in the
codebook), such as displaying information in a more visible way (“Elmo projectors allow
teachers to effectively display information so that all students are able to see it”), supporting
research (“It is valuable because the opportunities for exploration and research are endless”),
accessing more information (“The internet will just give additional information”). Other frequent
evidence cited was motivating students (“It [technology] is also something of interest to them
[students]”; #1 in codebook) and using technology to support lesson planning (“It’s valuable to
me to see new teaching ideas and creative lesson plans”; #14 in codebook).

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TPK
Respondent #

TK
CK
TCK
PK
PCK

Knowledge References in Rationale

Figure 1. Visualization of Depth of Rationalization. Cumulative Number of Knowledge Types
Evidenced in each Rationale by Fall 2008 Respondents

TPK

Respondent
#

TK

CK

TCK

PK

PCK

Knowledge
References
in
Rationale


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Evidenced in each Rationale by Spring 2009 Respondents

TPK

Respondent
#

TK

CK

TCK

PK

PCK

Knowledge
References
in
Rationale

Evidenced in each Rationale by Fall 2009 Respondents
There are only a handful of rationales evidencing TPACK depth (e.g., including more
than 1-2 ideas that represent more than 1-2 types of knowledge). Respondent #2 and #18 in fall
2008 used five explanatory ideas, the brackets, to support their rationale, but all ideas were TPK.
LT: Microsoft Applications: Word, Powerpoint, Excel:
Rationale: Word can be used [to write lesson plans,] [help students publish work],
[communicate with students and parents.] Excel can be used [to organize data and create
graphs of student progress.] [Powerpoint can be used to supplement lessons - the visuals
it can help teachers create are great!] (Respondent #2, Fall 2008)

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Respondent #25’s rationale included three explanatory ideas reflecting TCK, PK, and PCK.
LT: [Video clips usually from Youtube.]
Rationale: [In English students almost always read Shakespeare,] and [it is hard to read
something that is suppose to be performed and get students actively engaged in the
content] (Respondent #25, Spring 2009)
This rationale shows depth, as the respondent begins referencing her content knowledge:
Shakespeare is taught in English. She then referenced her PCK: It is difficult to engage students
in reading texts that are meant to be performed. In this case, the YouTube videos, which we infer
are theater productions of Shakespeare, are a form of TCK, a content ICT that would not be
applicable in another content area.
Respondent #11 from fall 2009 shows more depth within her rationale, citing four
explanatory ideas that reference TPK, TK and PK.
LT: I have to say that I became much more comfortable with Powerpoint throughout my
teacher preparatory semesters. I also really enjoyed learning how to make an imovie.
Rationale: [I have used numerous Powerpoint presentations in my college classes as well
as in my placement.] Just recently [I was able to make a Powerpoint slide show showing
the first graders pictures of kids in Ghana.] [We talked about the similarities and
differences between our school and theirs.] [I also was able to help a group of third

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graders with their imovies on animals. I felt confident enough to answer their questions.]
(Respondent #11, Fall 2009)
The respondent indicates her TK (use of PowerPoint and iMovie) as well as TPK when she
describes making a PowerPoint to show students pictures. Finally, she references PK when she
describes a general pedagogical technique of facilitating a similarity/difference discussion.
In summary, we found across these cohorts, preservice teachers found presentation
software, computers, laptops, Internet access, computer projectors, document cameras, and
online video content to be most frequently identified as most valuable. Preservice teachers
identified teacher-centric learning technologies 3 times more often than student-centered uses.
When rationalizing their valued learning technologies, respondents predominantly drew upon
their TPK, TK, and PK. Their rationales tended to lack breadth by reference to only one or two
reasons and use of only one or two knowledge types.
Discussion and Future Research
Across these cohorts, productivity activities (e.g., Word, PowerPoint) dominated as the
ICT most used for educational purposes, while communication activities are the most used
overall (60% report use) and most frequently used at a daily to weekly basis. Creation and web
activities (e.g., digital art, audio, and video, web pages, podcasting) tend to be associated with
Web 2.0 affordances (Greenhow, Robelia, & Hughes, 2009; Jenkins, 2006) that support creation,

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collaboration, and co-construction of knowledge–activities that may be more student-centered.
While only 38% of the graduates reported using creation activities, it is promising that they used
creation tools almost equally for personal and educational purposes. Across these results, I worry
about the domination of productivity activities and teacher-centric uses mainly because there are
many other media activities that are also worthwhile for technology integration efforts and likely
provide more content-specificity for student use, the essence of my definition of technology
integration. Kay’s (2007a) study of preservice teachers in a laptop program also found a
predominance of teacher uses, such as creating lesson plans, handouts, worksheets, resources,
and searching the web for teaching ideas, and student uses, such as engaging in Internet research
or word processing. Preparation programs need to extend beyond productivity software and
begin articulating, supporting, leveraging, and modeling how new media and its capabilities
(Martinez, 2010), such as those used in creation and web activities in this study, can be used in
content-area teaching for student learning. While no typical range or depth of media activity use
for a teacher graduate has been identified, I believe exposure to ICTs is extremely important.
Enabling all graduates to have engaged in a wide range of contemporary ICT activities at some
frequency level could provide more images of the possible for ICT to play a role in teaching and
learning (Hughes, 2004). In this way, novice teachers will have more experience evaluating and
considering new digital technologies, perhaps moving beyond the entrenched productivity tools,

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to be better prepared for a range of technological resources that may be available at their future
school.
Despite the fact that current society uses a range of contemporary ICTs, such as data
visualization, geomapping, and transmedia storytelling, to solve problems and create new
knowledge through creativity, collaboration, critical thinking, and visualization, this study
reveals that preservice teachers in a technology-rich preparation program are predominantly
exposed to and report using the same technological activities (i.e., PowerPoint, Word, Internet)
as preservice teachers reported five years ago (Kay, 2007a) and 12-15 years ago (Moursund &
Bielefeldt, 1999; Willis & Mehlinger, 1996). Even after years of technological advancements in
society and time for technological adoption and transformation, this case study reveals preservice
teacher graduates with a technological experience base similar to graduates from the last fifteen
years.
The analysis of the respondents’ rationalization for their most valuable learning
technologies indicates a well-developed sense of TPK, yet they generally do not draw on more
than TPK to explain their valued learning technologies. This result might have occurred because
productivity activities, reported most often used for educational purposes by respondents, are
often adopted for general pedagogical purposes. The rare mention of content-specific
technologies as most valued may indicate lack of exposure to content-specific technologies,

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which would limit development of TCK, CK, and ultimately TPACK. Alternatively, this result
may be considered developmentally-appropriate even in a technology-rich setting, as OzgunKoca et al. (2010), whose study was set in a technology-rich math methods course, found
preservice teachers’ initial attempts to integrate technology were “naïve and incorporate[d]
technology superficially” (p. 18). It appears there is great difficulty for beginning teachers to
identify, understand, and value technology that supports content-specific teaching and learning.
It also appears to require more than cursory exposure.
Some researchers are investigating what learning experiences during preservice
preparation might develop depth of knowledge beyond TPK. Cavin and Fernandez (2007) found
microteaching lesson study with instructor modeling assisted in developing TPACK. Borko et
al.’s (2009) special issue on uses of technology for teacher learning revealed that media
experiences, especially with video, enables preservice teachers to critically analyze students’
thinking, self-reflect about their teaching, and examine the complexity of teaching in
multiple/varied contexts (Hatch, Sun, Grossman, Neira, & Chang, 2009; Rich & Hannafin, 2009;
Santagata, 2009; Sherin & van Es, 2009). Advances in digital video now allow recording and
analysis of one’s own teaching experiences (e.g., Calandra & Brantley-Dias, 2010; Rosaen,
Lundeberg, Cooper, Fritzen, & Terpstra, 2008; Sherin & van Es, 2005; Yerrick, Ross, &
Molebash, 2005). Further research is needed to see if and how these video and media-based tools

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for inquiry, reflection, and noticing might promote preservice teachers’ greater awareness of and
development of knowledge, such as TPACK, and how such knowledge might inform practice.
This research area is, as of yet, unexplored.
This case study reveals graduates with moderately positive digital technology selfefficacy and attitudes towards learning technologies but markedly non-contemporary digital
technology experiences that focus on productivity technologies like PowerPoint, Word, and web
searching. One way to grapple with the evidence of productivity predominance and naïve and
less-complex TPACK among preservice teacher graduates is to consider TPACK a life-long
learning pursuit. Thus, teacher educators should expect after teacher preparation, some evidence,
perhaps similar to what is evident in this research, that preservice teachers are developing
TPACK and beginning to use such knowledge to think about how to teach with technology for
content-specific purposes. However, more TPACK development should occur as novice teachers
become more experienced. Future research should involve longitudinal study of graduates’
experiences from preservice into novice and veteran teaching, which can provide better evidence
of the long-range impact of the technological preparation of teachers and ongoing development
in specific teaching contexts.
Positioning TPACK development as a life-long learning process, however, should not
abdicate teacher education institutions’ responsibility in supporting such development through

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content-rich, contemporary technological experiences. Such an environment needs to involve (a)
unrestricted ubiquitous access to digital technologies, especially content-specific technologies,
with annual purchases to refresh resources; (b) ample technical support; (c) university faculty
who model content-specific technology integration across program experiences; (d) ongoing
faculty technology development, of which most is content-specific; and (e) strong partnerships
with PK-12 schools to increase opportunities for technology-rich field placements and student
teaching opportunities. Establishing these programmatic elements begins the process of
technological development for preservice teachers. A technological induction program that
begins upon initial placement as a new teacher would support the continued development of
teachers’ TPACK. The induction program might involve cohorts of content or grade-specific
teachers who could work closely with PK-12 technology or curriculum specialists and/or content
and technology integration scholars. Teachers would use problems-of-practice to investigate
role(s) digital technologies might play in content-specific student learning while considering
their contextual challenges. Cohort members might engage in technology-infused
lesson/case/problem study (Hughes, 2005; Mouza & Wong, 2009; Stigler & Hiebert, 1999; Tee
& Lee, 2011) or reflective writing in a supportive group environment that offers ample access to
class sets of content-specific digital technologies. In this way, teaching with technology becomes
a life-long learning pursuit that may reflect contemporary technological advancements in society.

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Limitations
A case study naturally limits statistical generalizability of the results. By focusing on and
describing the technology-rich laptop preservice program setting, reader-based generalization of
the results, common in qualitative data and case studies (Firestone, 1993), may occur. If
preservice teacher preparation programs aim to provide preparation that is current with societal
expectations and trends such as mobile computing within PK-12 schools (Johnson, Adams &
Haywood, 2011), teacher preparation programs need to become more technologically ubiquitous.
Research within technology-rich preservice settings, such as this case study, may provide key
understandings to support redefining and redesigning preservice programs to explicitly build
content-focused, ubiquitous, technology integration expertise within graduates.
The prolonged engagement with the program, as evidenced in three participating cohorts
across two years’ time, serves to increase trustworthiness of the results (Creswell, 1998).
Including multiple forms of data (observations and interviews) and a range of informants (e.g.,
faculty and field coordinators) in addition to the self-reported data I was able to collect in this
study would have enabled more triangulation, further increasing trustworthiness of the results.
Greater funding for research on teacher education, a rare priority for funding agencies (CochranSmith & Zeichner, 2005), would allow for fewer limitations in research design, enable the field
to answer more questions, and yield more trustworthiness and credibility in the findings.

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Appendix: TPACK Codebook
Technological Pedagogical Knowledge (TPK)
Evidence:
1. Motivating students through technology
2. Differentiating instruction when technology is used
3. Ability to organize collaborative work with technology
4. Holding students accountable for equipment used
5. Developing strategies for assessing student work with technology
6. Knowing about the existence of a variety of technological tools for particular general
pedagogical tasks
7. Ability to choose a tool based on fitness with content and learning goals 3
8. Ability to repurpose commercial software for general teaching
9. Knowing about the time required to teach with particular technologies
10. Ability to envision potential student problems with particular technologies and plan
relevant activities to support those students
11. Generating alternatives in the event of technological failures
12. Ability to explain a computer procedure to students (e.g., through modeling)
13. Knowledge of NETS-S – expectations for students’ technological literacy
14. Using technology for lesson planning preparation
15. Using technology for general assessment (e.g., grading, portfolios)
16. Knowledge of infrastructure at school site
Technology Knowledge (TK)
Evidence:
1. Operating computer hardware
2. Using standard software tools (e.g., MS Word etc.) for non-educational use
3. Installing and removing peripheral devices (e.g., USB drives, microphones etc.)
4. Troubleshooting equipment
5. Using appropriate vocabulary
6. Knowledge of current and emergent technologies in society
Content Knowledge (CK)
Evidence:
1. Knowledge of concepts, principles, and relationships in a curricular domain
2. Knowledge of the rules of evidence and proof

3
We removed this code from our codebook but did not reassign the Evidence number (7) in
order to facilitate cross-study comparison, if applicable.

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Technological Content Knowledge (TCK)
Evidence:
1. Knowing about the existence of a variety of content tools for particular content tasks;
especially tools that experts in this field might use.
2. Operating / knowledge of content-based technologies in which content learning is
foregrounded
3. Knowledge about the ways in which content and technology reciprocally related to one
another
Pedagogical Knowledge (PK)
Evidence:
1. Knowledge of general teaching methods and strategies
2. Checking for understanding
3. Knowledge of learners and their background
4. Knowledge of general assessment strategies (e.g., tests, oral, project-oriented tasks)
5. Classroom management techniques
6. Lesson planning activities and preparation
Pedagogical Content Knowledge (PCK)
Evidence:
1. Knowledge of teaching /representing subject matter to students (e.g., techniques,
representations, analogies)
2. Identifying and addressing student subject-specific misconceptions or mistakes
3. Content-specific assessment strategies

37

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References
Allsopp, D. H., McHatton, P. A., & Cranston-Gingras, A. (2009). Examining perceptions of
systematic integration of instructional technology in a teacher education program.
Teacher Education and Special Education, 32(4), 337-50.
Anderson, S. E., & Maninger, R. M. (2007). Preservice teachers' abilities, beliefs, and intentions
regarding technology integration. Journal of Educational Computing Research, 37(2),
151-172.
Anderson, S. E., Groulx, J. G., & Maninger, R. M. (2011). Relationships among preservice
teachers' technology-related abilities, beliefs, and intentions to use technology in their
future classrooms. Journal of Educational Computing Research, 45(3), 321-338.
Angeli, C., & Valanides, N. (2005). Preservice elementary teachers as information and
communication technology designers: An instructional systems design model based on an
expanded view of pedagogical content knowledge. Journal of Computer Assisted
Learning, 21(4), 292-302.
Angeli, C., & Valanides, N. (2009). Epistemological and methodological issues for the
conceptualization, development, and assessment of ICT-TPCK: Advances in
Technological Pedagogical Content Knowledge (TPCK). Computers & Education, 52(1),
154-168.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change.
Psychological Review, 84(2), 191-215.
Becker, H. J., & Anderson, R. E. (1998). Teacher's survey: Combined versions 1-4. In Teaching,
learning and computing: 1998 survey. Irvine, CA.
Borko, H., Whitcomb, J., & Liston, D. (2009). Wicked problems and other thoughts on issues of
technology and teacher learning. Journal of Teacher Education, 60(1), 3-7.
Brinkerhoff, J. (2006). Effects of a long-duration, professional development academy on
technology skills, computer self-efficacy, and technology integration beliefs and
practices. Journal of Research on Technology in Education, 39(1), 22-43.
Calandra, B., & Brantley-Dias, L. (2010). Using digital video editing to shape novice teachers: A
generative process for nuturing professional growth. Educational Technology, (1), 13-17.
Carter, K. (1990). Teachers' knowledge and learning to teach. In W. R. Houston, M. Huberman
& J. Sikula (Eds.), Handbook of research on teacher education (pp. 291-310). New York:
MacMillan.
Cassidy, S., & Eachus, P. (2002). Developing the Computer User Self-Efficacy (CUSE) scale:
Investigating the relationship between computer self-efficacy, gender, and experience
with computers. Journal of Educational Computing Research, 26(2), 133-153.

INTEGRATION

39

Cavin, R., & Fernandez, M. (2007). Developing technological pedagogical content knowledge in
preservice math and science teachers. Technology and Teacher Education Annual, 18(4),
2180.
Chen, R. (2010). Investigating models for preservice teachers' use of technology to support
student-centered learning. Computers & Education, 55(1), 32-42.
Clift, R. T., Mullen, L., Levin, J., & Larson, A. (2001). Technologies in contexts: implications
for teacher education. Teaching and Teacher Education, 17, 33-50.
Cole, M. (1996). Cultural psychology: A once and future discipline. Cambridge, MA: Harvard
University Press.
Cochran-Smith, M., & Zeichner, K. M. (Eds.). (2005). Studying teacher education. The report of
the AERA Panel on Research and Teacher Education. Mahwah, NJ: Lawrence Erlbaum.
Common core state standards for English Language Arts & Literacy in History/Social Studies,
Science, and Technical Subjects. (2010a). Retrieved June 14, 2011, from
http://www.corestandards.org/
Common core state standards for Mathematics. (2010b). Retrieved June 14, 2011, from
http://www.corestandards.org/
Cox, S., & Graham, C. R. (2009). Diagramming TPACK in practice: Using an elaborated model
of the TPACK framework to analyze and depict teacher knowledge. TechTrends, 53(5),
60–69.
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions.
Thousand Oaks: Sage.
Cullen, T. A., & Greene, B. A. (2011). Preservice teachers' beliefs, attitudes, and motivation
about technology integration. Journal of Educational Computing Research, 45(1), 29-47.
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge,
confidence, beliefs, and culture intersect. Journal of Research on Technology in
Education, 42(3), 255-284.
Ertmer, P. A., Ottenbreit-Leftwich, A., & York, C. S. (2006-2007). Exemplary technologyusing teachers: Perceptions of factors influencing success. Journal of Computing in
Teacher Education, 23(2), 55-61.
Firestone, W. A. (1993). Alternative arguments for generalizing from data as applied to
qualitative research. Educational Researcher, 22(4), 16-23.
Friedman, A., & Kajder, S. (2006). Perceptions of beginning teacher education students
regarding educational technology. Journal of Computing in Teacher Education, 22(4),
147-151.
Fullan, M. (2007). The new meaning of educational change (4th ed.). New York: Teachers
College.

INTEGRATION

40

Graham, C. R. (2011). Theoretical considerations for understanding technological pedagogical
content knowledge (TPACK). Computers & Education, 57(3), 1953-1960.
Greenhow, C., Robelia, B., & Hughes, J. E. (2009). Learning, teaching, and scholarship in a
digital age: Web 2.0 and classroom research: What path should we take now?
Educational Researcher, 38(4), 246-259.
Greeno, J. (1989). The situativity of knowing, learning, and research. American Psychologist, 53,
5–26.
Greeno, J. G., Collins, A., & Resnick, L. B. (1996). Cognition and learning. In D. Berliner & R.
Calfee (Eds.), Handbook of educational psychology. New York: MacMillan.
Hatch, T., Sun, C., Grossman, P., Neira, P., & Chang (2009). Learning from the practice of
veteran and novice teachers. Journal of Teacher Education, 60(1), 68-9.
Holcomb, L., King, F. B., & Brown, S. W. (2004). Student traits and attributes contributing to
success in online courses: Evaluation of university online courses. The Journal of
Interactive Online Learning, 2(3), 1-16.
Hughes, J. (2004). Technology learning principles for preservice and in-service teacher
education. Contemporary Issues in Technology and Teacher Education [Online serial],
4(3). Available: http://www.citejournal.org/vol4/iss3/general/article2.cfm
Hughes, J. E. (2005). The role of teacher knowledge and learning experiences in forming
technology-integrated pedagogy. Journal of Technology and Teacher Education, 13(2),
277-302.
Jenkins, H. (2006). Confronting the challenges of participatory culture: Media education for the
21st Century. Chicago, IL: MacArthur Foundation.
Jimoyiannis, A. (2010). Designing and implementing an integrated technological pedagogical
science knowledge framework for science teachers’ professional development.
Computers & Education, 55(3), 1259-1269.
Johnson, L., Adams, S., & Haywood, K. (2011). The NMC Horizon Report: 2011 K-12 Edition.
Austin, Texas: The New Media Consortium.
Kay, R. H. (2006a). Evaluating strategies used to incorporate technology into preservice
education: A review of the literature. Journal of Research on Technology in Education,
38(4), 383-408.
Kay, R. (2006b). Addressing gender differences in computer ability, attitudes, and use: The
laptop effect. Journal of Educational Computing Research, 34(2), 187-211.
Kay, R. (2007a). The impact of preservice teachers' emotions on computer use: A formative
analysis. Journal of Educational Computing Research, 36(4), 455-479.
Kay, R. (2007b). A formative analysis of how preservice teachers learn to use technology.
Journal of Computer Assisted Learning, 23(5), 366-383.

INTEGRATION

41

Koh, J. H. L., & Divaharan, S. (2011). Developing pre-service teachers' technology integration
expertise through the TPACK-developing instructional model. Journal of Educational
Computing Research, 44(1), 35-58.
Lipscomb, G. B., & Doppen, F. H. (2004/2005). Climbing the stairs: Pre-service social studies
teachers' perceptions of technology integration. International Journal of Social
Education, 19(2), 70-87.
MacKinnon, G. R., Aylward, M. L., & Bellefontaine, J. (2006). Electronic discussion.
Computers in the schools, 23(1-2), 59-71.
Margerum-Leys, J., & Marx, R. W. (2002). Teacher knowledge of educational technology: A
case study of student/mentor teacher pairs. Journal of Educational Computing Research,
26(4), 427-462.
Martinez, M. (2010). How a new generation of teachers will change schools. Phi Delta Kappan,
91(7), 74-75.
Meyers, E. (2006). Using electronic journals to facilitate reflective thinking regarding
instructional practices during early field experiences. Education, 126(4), 756-762.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A
framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Moursund, D., & Bielefeldt, T. (1999). Will new teachers be prepared to teach in a digital age?
A national survey on information technology in teacher education. Santa Monica, CA:
Milken Exchange on Educational Technology. Available:
http://www.mff.org/publications/publications.taf?page=154
Mouza, C., & Wong, W. (2009). Student classroom practice: Case development for professional
learning in technology integration. Journal of Technology and Teacher Education, 17(2),
175-202.
Niess, M. L. (2005). Preparing teachers to teach science and mathematics with technology:
Developing a technology pedagogical content knowledge. Teaching and Teacher
Education, 21(5), 509–523.
Niess, M. L. (2011). Investigating TPACK: Knowledge growth in teaching with technology.
Journal of Educational Computing Research, 44(3), 299-317.
Overbay, A., Patterson, A. S., Vasu, E. S., & Grable, L. L. (2010). Constructivism and
technology use: findings from the IMPACTing Leadership project. Educational Media
International, 47(2), 103-120.
Ozgun-Koca, S. A., Meagher, M., & Edwards, M. T. (2010). Preservice teachers' emerging
TPACK in a technology-rich methods class. Mathematics Educator, 19(2), 10-20.
Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks:
Sage.

INTEGRATION

42

Polly, D., & Shepherd, C. E. (2007). Preservice teachers' perceptions of appropriate
technologies. In T. Kidd & H. Song (Eds.), Handbook of research on instructional
systems and technology (pp. 198-215).
Porter, A., McMaken, J., Hwang, J., & Yang, R. (2011). Common core standards: The new U.S.
intended curriculum. Educational Researcher, 40(3), 103-116.
Ravitz, J.L., Becker, H.J., & Wong, Y-T. (2000). Constructivist compatible beliefs and practices
among U.S. teachers. (Teaching, Learning & Computing Report 4.) Irvine, CA: Center
for Research on Information Technology and Organizations, University of California. .
[On-line]. Available: http://www.crito.uci.edu/TLC/findings/report4/
Rich, P.J., & Hannafin, M. (2009). Video annotation tools. Journal of Teacher Education, 60(1),
52-67.
Rosaen, C., Lundeberg, M., Cooper, M., Fritzen, A., & Terpstra, M. (2008). Noticing noticing:
How does investigation of video records change how teachers reflect on their
experiences? Journal of Teacher Education, 59(4), 347-360.
Sang, G., Valcke, M., van Braak, J., & Tondeur, J. (2010). Student teachers' thinking processes
and ICT integration: Predictors of prospective teaching behaviors with educational
technology. Computers & Education, 54(1), 103-112.
Santagata, R. (2009). Designing video-based professional development for mathematics teachers
in low-performing schools. Journal of Teacher Education, 60(1), 38-51.
Savery, J. R., & Reed, C. K. (2006). Wireless laptops for faculty: Boon or bane? Journal of
Technology and Teacher Education, 14(1), 167-172.
Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009).
Technological Pedagogical Content Knowledge (TPACK): The development and
validation of an assessment instrument for preservice teachers. Journal of Research on
Technology in Education, 42(2), 123-149.
Sherin, M., & van Es, E. (2005). Using video to support teachers’ ability to notice classroom
interactions. Journal of Technology and Teacher Education, 13(3), 475-491.
Sherin, M.G., & van Es, E.A. (2009). Effects of video club participation on teachers’
professional vision. Journal of Teacher Education, 60(1), 20-37.
Stake, R. E. (1995). The art of case study. Thousand Oaks: Sage.
Stigler, J. & Hiebert, J. (1999). The teaching gap. New York: Summit.
Students and information technology in higher education: 2008 survey questionnaire. (2008).
The ECAR Study of Undergraduate Students and Information Technology, 2008,
EDUCAUSE. Accessed June 15, 2008 from: http://www.educause.edu/ers0808

INTEGRATION

43

Tee, M.Y., & Lee, S.S. (2011). From socialisation to internalisation: Cultivating technological
pedagogical content knowledge through problem-based learning. Australasian Journal of
Educational Technology, 27(1), 89-104.
Thompson, A., Schmidt, D. A., & Davis, N. E. (2003). Technology collaboratives for
simultaneous renewal in teacher education. Educational Technology Research and
Development, 51(1), 73-89.
Tothero, M. L. (2005). University of Texas at Austin explores LIFE. T.H.E. Journal, 33(3), 4445.
Vygotsky, L. S. (1978). Interaction between learning and development. In Mind in society: The
development of higher psychological processes (pp. 79-91). Cambridge, MA: Harvard
University Press.
Wang, Y. (2002). When technology meets beliefs: Preservice teachers' perception of the teacher's
role in the classroom with computers. Journal of Research on Technology in Teacher
Education, 35(1), 150-161.
Willis, J., & Mehlinger, H. D. (1996). Information technology and teacher education. In J.
Sikula, T. J. Buttery & E. Guyton (Eds.), Handbook of research on teacher education
(2nd ed., pp. 978-1029). New York: Simon & Schuster Macmillan.
Yerrick, R., Ross, D., & Molebash, P. (2005). Too close for comfort: Real-time science teaching
reflections via digital video editing. Journal of Science Teacher Education, 16(4), 351375.
Zhao, Y., Pugh, K., Sheldon, S., & Byers, J. L. (2002). Conditions for classroom technology
innovations. Teachers College Record, 104(3), 482-515.

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