Understanding preservice teachers' technology ... - Wiley Online Library

Original article doi: 10.1111/j.1365-2729.2011.00447.x

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Understanding preservice teachers’ technology use through TPACK framework jcal_447

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S. Pamuk Computer Education and Instructional Technology Department, Ondokuz Mayis University, Samsun, Turkey

Abstract

This study discusses preservice teachers’ achievement barriers to technology integration, using principles of technological pedagogical content knowledge (TPACK) as an evaluative framework. Technology-capable participants each freely chose a content area to comprise project. Data analysis based on interactions among core components of TPACK revealed that participants struggled with developing new knowledge. Lack of pedagogical experience limited development of appropriate technology integration approaches. Creating new knowledge bases based on different teaching components can be difficult for preservice teachers because it requires a deep understanding of core knowledge and interpretation of the teaching context and its dynamics. Developing pedagogical content knowledge (PCK) is an important factor in overall technology integration; teachers must make it a priority to acquire PCK before integrating technology. In preservice teacher education, PCK development must be supported with actual teaching experience. We believe that the results of the study may provide valuable insight with respect to proper focus on technology integration and recognizing limitations and challenges within TPACK principles to both those who teach technology integration and those who design TPACK-based activities.

Keywords

pedagogy and technology, preservice teacher education, technology integration, TPACK.

Introduction

Teachers’ pedagogical beliefs and practices in the classroom are central to all teaching and learning activities (Macleod & Golby 2003; Ertmer 2005; Hammond 2006). In a multidimensional teaching structure, teachers may consider many factors (i.e. content they teach, student background, classroom activities) to compose a pedagogical approach and to optimally organize their activities (Shulman 1986, 1999). Also, the emergence of information technologies in the 21st century obligates teachers to revisit pedagogical beliefs and to re-arrange Accepted: 1 August 2011 Correspondence: Sonmez Pamuk, Computer Education & Instructional Technology Department, College of Education, Ondokuz Mayis University Atakum, Samsun 55200, Turkey. Email: sonmezp@ omu.edu.tr

© 2011 Blackwell Publishing Ltd

teaching activities accordingly. The results of early adopters’ use of technology indicate that this is not an easy task that teachers can accomplish through simple changes in approach (Bull et al. 2005; Brzycki & Dudt 2005; Hew & Brush 2007). Studies from the project Preparing Tomorrow’s Teachers to Use Technology in the United States investigated different dimensions of technology integration efforts and confirmed that effective technology integration is a multi-layer process and requires adjustments at different levels (i.e. student, teacher, colleges of education) (Thompson et al. 2003; Strudler & Wetzel 2005). Some important findings (Chuang et al. 2003; Wetzel & Williams 2004; Brzycki & Dudt 2005; Hall 2006) suggest steps such as moving from a stand-alone technology course to technology-integrated curricula and context-specific approaches, modeling of technology

Journal of Computer Assisted Learning (2012), 28, 425–439

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use by college educators, faculty development, and providing opportunities to prospective teachers to use technology. Although scepticism remains about technology use in education, there is a broad agreement among educators that technology can be effective and support learning only if it is meaningfully integrated into teaching. Mishra and Koehler (2006) offer a solution in the technological pedagogical content knowledge (TPACK) framework that basically emphasizes use of contextual pedagogy, content, and technology. TPACK detail is provided in the theoretical section. In this study, we aim at using TPACK to evaluate investigation of preservice teachers’ technology integration knowledge and abilities, and to identify areas of deficiency described within the TPACK theoretical framework. Theoretical section

Fig 1 Technological pedagogical content knowledge (retrieved from http://tpack.org).

The root of TPACK framework development goes back to Shulman’s pedagogical content knowledge (PCK) principles (Shulman 1986). Shulman (1987) stated that teachers must develop a new ‘knowledge base’ emerging from the relationship between content and pedagogy. Effective teaching requires more than isolated knowledge in content and in pedagogy. Context-free teaching approaches developed through isolated components eventually are bound to fail or will not effectively provide desired outcomes. Thus, a new PCK base emerges from the interaction between content and pedagogy in context with its unique properties. Shulman (1987) also stated that PCK ‘represents the blending of content and pedagogy into an understanding of how particular topics, problems, or issues are organized, represented, and adapted to diverse interests and abilities of learners, and presented for instruction’ (p. 8). Moving through this understanding of interactions between content and pedagogy and adding a new component to the traditional PCK schema require educators to define a new technology-based knowledge base. Mishra and Koehler (2006) inserted the technology component into Shulman’s PCK model to describe the relationship between technology and other components. Their model is called TPACK. It defines technology integration as a complex multidimensional process requiring understanding of the reciprocal dynamic rela-

tionships between three knowledge bases pedagogy, content, and technology. As represented in Fig 1, Koehler et al. (2007) pointed out that ‘at the heart of TPACK is the dynamic transactional relationship between content, pedagogy, and technology. Good teaching with technology requires understanding the mutually-reinforcing relationships between all three elements taken together to develop appropriate, context-specific strategies and representations’ (p. 741). Within the TPACK framework, content, technology, and pedagogy are respectively described as subject matter, as tools to be used in teaching to represent information (technology), and methods of teaching and evaluating student learning (pedagogy). Interactions and relationships among these elements are stressed as factors teachers must address in the technology integration process. Angeli and Valanides (2009) reviewed TPACK literature and stressed the importance of the relationship between components: ‘all existing views (on TPACK) are founded on the common principle that effective technology integration presupposes conceptualizations that must be necessarily formulated by considering the interactions among technology, content, and pedagogy’ (p. 155). For those relationships, Koehler et al. (2007) mentioned that technology addresses pedagogical © 2011 Blackwell Publishing Ltd

Preservice teachers’ technology use

issues by providing teachers alternatives for representing concepts they teach in different and rich forms, by strengthening prior knowledge, etc. Similarly, Angeli and Valanides (2009) also emphasized the role of technology intended ‘to transform content and pedagogy for learners’ (p. 156). Although literature on the TPACK framework provides educators descriptions of conceptual models on technology integration, the importance of each component given in the framework, the nature of the relationships, interactions with each knowledge base, and problems that arise from implementation (Cox 2008; Angeli & Valanides 2009; Archambault & Barnett 2010; Graham 2011), we have only limited understanding and research on use of the TPACK theoretical framework as an evaluative tool for understanding preservice teachers’ technology integration knowledge and abilities and related issues. It is especially important to understand the process of development of knowledge bases, interactions among components (T, P, C) and, more importantly, how lack of knowledge in one knowledge domain can negatively impact an overall technology integration effort. We therefore believe that this research approach is very important, especially for teacher educators in charge of teaching or modeling effective technology integration for those with limited knowledge and experience in different knowledge domains. Using TPACK theoretical lenses to understand preservice teachers’ knowledge, and to provide a strategy for interaction among different components (T, P, C), and experiences would provide valuable insight for organizing and teaching preservice teachers, effective technology integration strategies before they proceed into service. In this study, the main emphasis was placed on the question of understanding how preservice teachers – with limited knowledge in any dimension of the teaching task – can integrate technology into teaching, and thereby impact the overall technology integration effort.

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and informal observations) detailed in Table 1 were used for data collection. Research context

This study was conducted within a computer education and instructional technology department at a Turkish university. Because of the institutional structure and 4-year curriculum, all participants in this study had virtually the same programme of study with both educational (i.e. educational psychology, special teaching methods) and technology courses (i.e. database systems, web programming). The current study involved 78 juniors in a semesterlong course, Principles of Distance Education. This course included weekly 2-h lectures and a 2-h lab. The lecture portion of the course was organized around teaching principles of distance education, with project work performed during lab hours. The data were collected from two different sections of the same course. Preservice teachers were required to develop educational materials for teaching subject matter to learners who are either distant-located or are using computers independently. Participants were allowed to choose the subject matter they would like to teach with technology, so there was variation in content areas and target populations. Data collection and analysis procedures in this study were focused on how preservice teachers in each context used their technical and pedagogical backgrounds to create new TPACK knowledge bases. Participants

The participants in this study consisted of 78 preservice teachers. All were juniors and took virtually the same courses. Graduates of this programme would expect to achieve responsible positions as technology teachers, mostly at the middle or high school level, or in positions such as web designers, technical support staff, or network support personnel.

Methodology

A basic interpretative qualitative research approach was selected to enable understanding of preservice teachers’ approaches to knowledge base creation processes. Multiple data sources and tools (i.e. open-ended questionnaires, teaching products, final project report, formal, © 2011 Blackwell Publishing Ltd

Data collection process

Multiple techniques were employed to collect data in a two-stage process. In the first stage, data (from sources #1 through #5 in Table 1) were used to create categories and develop initial findings. These findings were shared

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Table 1. Data collection tools and sources. Data sources

Definition/example

1. Participatory informal observations

Course instructor (researcher) had opportunity to observe class and lab participants during a week for about for 4 h total for each section of the course. At the beginning, the researcher did not code the data, but did so electronically from memos immediately after each class. Example: Code → Pedagogical approach (Beliefs) ‘When I asked students how they define their future teaching approach, they mostly talked about the terms “behavior change”, “positive reinforcement”, “punishment”, etc.’ Code → Technology and content ‘Today, students at the lab were mostly worked on preparing presentation of the content in such forms as PowerPoint.’ Based on the analysis of the data from informal observations, interviews, literature review, and other artefacts, a 14-item open-ended questionnaire was developed and administered at the end of each semester. Resulting data were specifically used as a confirmatory source in finalizing conceptual categories. Example: Do you have any idea on possible teaching approaches that would be effective teaching this selected topic? What teaching approaches and strategies would you recommend? How does technology support your teaching style and at what dynamics of your teaching were enriched with technology? Outline was prepared and provided by the researcher. Participants turned in reports at semester end. Sections from project report outlines were ‘pedagogic approach’ and ‘role of technology, assessment strategies’. Participants prepared technology-based teaching material for distance education use (see Fig 2), and wrote a paper defining learning. Projects were evaluated based on supplied criteria (i.e. appropriateness of the visual design, pedagogic approach, project-learner interaction, content presentation, and assessment strategy). Projects evaluated and graded at the end of the semester. Example: Does the project include any instructional activity so that learners interact with the content? What kind of evaluation strategy was implemented for assessment of students’ learning? Informal conversations with participants in class and at lab sessions. Important data were noted, as were observations. Example: Student: I use multiple-choice test as the assessment tool in my project. Researcher: Why do you want to use multiple-choice tests as the assessment strategy rather than use of concept map or something else? Researcher: Do you think that there is any difference between book content and content given on your project. Initial research findings were shared with all participants through an online databasedriven website, agreement levels (Agree, Neutral, Disagree), and their reflections about each finding were collected. Forty-nine participants shared their thoughts.

2. Open-ended questionnaire

3. Project report

4. Student teaching materials /artefacts

5. Unstructured informal interviews

6. Second phase of data collection and online member check

with participants in the second stage to support conceptualization of their experiences and provide an opportunity for reflection. The participants’ reflections and feedback on the findings provided evidence of the study’s validity.

One-semester first-stage data collection began with informal observations (#1 in Table 1). This was immediately followed with informal interviews, conversations, and discussions with participants (#5). In each lab session, there was a one-to-one relationship between the © 2011 Blackwell Publishing Ltd


researcher and participants. Preservice teachers’ questions, ideas, and thoughts about their projects were valuable data sources, especially for understanding their pedagogical approaches. Gall et al. (1999) describe such interactions as informal interviews, and the nature of these interviews made it difficult to record their exact number. During the early weeks, the researcher was mainly interested in general-behaviour data. During later weeks, there was increased focus on items like pedagogical and technological issues, use of technology, and other issues. The data collection process was followed by examining documents (#4) collected during the early weeks of the semester identifying participants’ views on learning and the role of technology. Towards the end of the semester, data were mainly related to evaluation of students’ projects (#4) by the researcher. Once all these steps were completed, students were asked to answer the researcher’s online 14-question questionnaire (#2). Sixty-seven participants responded to this questionnaire, and students’ final project reports were collected and analysed at the end of the semester (#3). Following the first data collection stage, data were analysed and initial findings shared with participants in the second stage through a database-driven website. Students rated their agreement level with each finding and could also provide their own reflections. Data analysis

Principles of grounded theory research methodology were employed throughout this study. A constantcomparison technique was used for data analysis (Glaser & Strauss 1967), as further recommended by Glaser (1978). In this approach, the researcher constantly compares incoming data to initial data. During the process, the researcher moves between data and initial analysis results and can determine needs for additional data, how to collect it, and the best source (Glaser & Strauss 1967; Merriam 2002). Data analysis is facilitated by three procedures: open coding, axial coding, and selective coding (Strauss & Corbin 1990; Jones & McEwen 2002). In the coding stage, initial categories are created by breaking down the data (open coding), followed by comparisons and relationships among them (axial coding), and, finally, using selective coding to finalize category generation and better understand the overall data. For example, © 2011 Blackwell Publishing Ltd

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data could be labelled ‘technology focus’ or ‘technology-oriented design’ using open coding, and then could be grouped as ‘technological ideas’ using axial coding. Finally, a selective coding procedure made it possible to select among general categories and concepts to develop an overall description of the preservice teachers’ TPACK knowledge base experiences. A triangulation strategy for data from different sources was used in this study as a means of providing qualitative research reliability and validity. Using this strategy, according to Merriam (2002), ‘a researcher collects data through a combination of interviews, observation, and document analysis’ (p. 25). Gall et al. (1999) defines triangulation as ‘the process of using multiple data-collection methods, data sources, analysts, or theories to check the (findings)’ (p. 305). Multiple data sources were implemented for this purpose. Observational data, for example, were not used to create a category until it was supported by interviews, questionnaire responses, or project reports. A second strategy for ensuring validity was member checks (Gall et al. 1999). After data were analysed and initial results and conclusions constructed, internetbased findings were shared with participants (#6 in Table 1). Participants’ reviews of research findings were also shared. Participants were asked to select one of three options (Agree, Neutral, Disagree) listed next to the each statement and to share additional thoughts in a text box. Forty-nine (63%) of 78 participants shared their thoughts. Before finalization of the study, data were assessed and used to construct the overall results. Adequate engagement and rich and thick study descriptions are other strategies listed by Merriam (2002) for achieving reliability and validity of qualitative research, and these methods were taken into consideration and used in this study. Results

The structure of the TPACK is hierarchical and begins with defining the core knowledge basis (P, C, T) required for teaching with technology. In this study, we first examined preservice teachers’ core knowledge adequacy as the foundation of the overall structure, then moved on to investigation of the knowledge basis through interactions such as technological pedagogical knowledge (TPK) and PCK. The final step was determining interactions among individual knowledge

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Table 2. Overall findings organized according to TPACK components. Knowledge Summary of findings base CK PK

TK

PCK

TCK

TPK

TPACK

• Participants did not mention any problems with chosen subject matter. They reported that they were all comfortable with their knowledge on the subject matter they chose. • Preservice teachers prefer to see more observable outcomes as learning indicators. Major factor from classroom discussions was overall academic culture and courses taken. When students pushed to go into more detail in their definitions and the learning process, lack of foundation in preservice teachers’ knowledge of subject was obvious. • A clear picture that, although students demonstrated limited pedagogical understandings and knowledge, it was not well grounded in the theoretical definitions. • Projects revealed that knowledge base in pedagogy or learning theories does not necessarily mean one is able to use technology as planned. • Academic culture of individual participants had major impact on their views on learning and teaching. • Before the study, participants were in a major programme requiring them to take many advanced technology courses. So, having no major problems with technology was an expected outcome and previously planned assumption. • Participants were knowledgeable in the content area they chose and in general teaching strategies, but they had difficulties or limitations in effectively combining these two knowledge elements. The major deficiency revealed was a lack of pedagogical experience in teaching. • Participants were mostly in favour of using technology to visualize content without any judgment about its effectiveness. • Preservice teachers were much more interested in technological than in educational ideas. Some preservice teachers had not demonstrated any experience or approach for deciding how to most effectively use technology to convey or transform content. • Many participants demonstrated use of technology as a means of linear information conveyance and used testing as a major assessment strategy. • Preservice teachers in this study reported no major problem with technology except for lack of pedagogical experience. Therefore, this limitation resulted in limited prior use of technology for transforming, supporting, or enriching pedagogical ideas and, eventually, creating technological pedagogical knowledge. • Participants favoured emphasis on technological ideas rather than combining them with educational ideas. • Lack of pedagogical experience and understanding of different teaching strategies were two major issues in developing the TPACK knowledge base. • Although preservice teachers’ pedagogical knowledge base initially seemed to be the only limitation, its impact on the creation of the other knowledge bases (i.e. TPK or PCK) and the creation of the TPACK became a crucial factor.

CK, content knowledge; PCK, pedagogical content knowledge; PK, pedagogical knowledge; TCK, technological content knowledge; TK, technological knowledge; TPACK, technological pedagogical content knowledge; TPK, technological pedagogical knowledge.

domains [TPK, PCK, technological content knowledge (TCK)] to define TPACK. The results of the study will therefore be presented in three main sections: overall findings, core knowledge basis, and knowledge basis from interactions.

Overall findings

This section summarizes the findings for each TPACK component. We first developed initial findings that became the overall findings from the data analysis (Table 2), and then initiated a second process stage by sharing these findings online with participants. While the majority of the participants (75%) indicated overall

agreement with the findings, 15% were neutral, and 10% disagreed with them. Core knowledge basis

This section provides details about preservice teachers’ knowledge and experiences on technology, pedagogy, and content. Participants’ agreement levels with each statement related to the core knowledge areas are also discussed (see Appendix A). Content knowledge Content knowledge is described as ‘understanding of the major facts and concepts in a discipline as well as the © 2011 Blackwell Publishing Ltd


substantive and syntactic structures of that field’ (Cox 2008, p. 7). Participants did not mention any problems or limitations within their projects with regard to the content they chose, and with all reporting comfort with their knowledge with respect to chosen subject matter. Participants’ agreement levels in Table A1 (see Appendix A) along with conclusions related to the content knowledge domain in Table 2 also confirm our conclusion about students’ comfort level with respect to content. While a large majority (90% of 49) of the participants reported that they agreed with the statement, four of the participants did not, but provided no explanation for their disagreement. Several participants stated in their project reports, I have adequate knowledge on the subject matter I chose for my project. As a specific example, one gave an assessment of adequacy of content knowledge. She pointed out that, I have used the main concepts of the subject matter I chose in my project. I believe that I have adequate knowledge on geometry since I like it and enjoy teaching it. Another student whose project focused on teaching English shared similar experiences. She stated, I think that I have enough knowledge at the level at which I teach in my project, since I like English and have been learning myself. Questionnaire data provided some insight on participants who felt lacking in content knowledge. One, for example, stated, I don’t think I have enough knowledge on punctuations in Turkish. I have always problem with using punctuations in my writings. But, I’ve learned during this project. Another participant indicated in the open-ended questionnaire discomfort with the subject matter because it was outside his or her area of specialization. Based on those participants’ thoughts and experiences, it could be concluded that some of the participants initially feel they have subject-matter knowledge but encounter unexpected limitations as they move forward. In addition to participants’ knowledge level or adequacy on the content emerged as the major category and discussed above, themes such as diversity of the content, structure of the content, and some others were also generated from data. Pedagogical knowledge (PK) PK is defined as ‘general skills, beliefs, and knowledge related to teaching, independent of a particular subject area. Knowledge and beliefs about learners, basic prin© 2011 Blackwell Publishing Ltd

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ciples of instruction, classroom management, and the aims and purposes of education are all part of general pedagogical knowledge’ (Cox 2008, p. 7). Shulman differentiated general PK from PCK, so the definition given here would be categorized as general PK. With regard to PK, we established several data categories (i.e. pedagogical approach, pedagogic adequacy, preferences, understanding, and limitations). Among these categories, participants’ comfort level with overall teaching and implementation of chosen pedagogical principles into project emerged as critical ones to be discussed in this section. Participants’ overall agreement level with regard to findings related to PK in Table 2 reveals that most participants (70%) had limited knowledge or experience on pedagogical issues, experiencing problems integrating them into teaching. Although student responses to the questionnaire (#2) and thoughts expressed in the document (#4) showed that they felt a certain level of competence in different teaching approaches and learning theories, their understanding was not implemented as expressed in their project reports. Specific issues like interactions, assessment strategies, collaboration, and others were not appropriately implemented in their projects. For example, one responded as follows: I preferred to use a cognitive teaching style in my project. Since there are individual differences in learning, I wanted to reach out to more people (by using cognitive teaching style). I believe that (by following this approach) I accomplished my purpose.

Another noted: It was impossible for me to use constructivist or behaviorist teaching approach in my project. Therefore, I used a cognitive teaching approach. To get the attention of learners, I underlined the more important points in the project. I used concept maps to transfer the information to learners. I also use strategies to provide advanced learning opportunities by allowing learners during analysis, implementation, and sentence activities.

In addition to students who expressed their pedagogic strategies in more theoretical terms, others discussed their teaching approaches with technology in such terms as visualization of the teacher/learner interaction with content and use of real-life cases in teaching. Data analysis within the terms of TPACK, also using Shulman’s PCK framework, revealed a clear picture that, while students demonstrated some pedagogical

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understanding and knowledge, it was somewhat limited and ungrounded in the theoretical definitions. Differences between students’ questionnaire self-reporting and their ability to integrate pedagogical strategies into their teaching revealed that having a knowledge base in pedagogy or learning theories does not necessarily mean one is able to use technology properly. As Cox (2008) discussed, the issue is moving from knowing to doing. Creating a TPK base, therefore, was problematic for participants in this study. Details are provided in the TPK section. Technological knowledge (TK) Technology knowledge is defined as the knowledge of different information technologies that would be used in daily life. A unique aspect of this research was that participants had strong backgrounds in software and hardware technologies, permitting a strategy focused on students’ technology integration ability and determining major factors beyond technology knowledge and skills. Major themes generated from the data were technology selection, software and hardware technologies knowledge, and technology knowledge level with respect to adequacy of technology. Because of the variety of technology selected, confidence with use of technology is also discussed in this section. Participants indicated that they all had general software and technology knowledge. Sixty-one per cent agreed that they had no major problem with technology during the development of their projects. Several, however, indicated both in questionnaire (#2) and project report paper (#3) responses that they learned new software functions during the project design. A considerable number of participants (25%, Disagree) did oppose or were undecided (14%, Neutral) on the technological adequacy findings. However, in examining their responses in the open-ended sections, we found that they did not directly reject the statement but rather doubted their level of efficacy in use of technology. As one participant noted that, I think that this is the main reason [lack of technology knowledge and experience] why we can’t move from theory to implementation. We can’t benefit from all potentials of technology as much as we need. One of the few neutral or undecided students, on the other hand, stated that, the changes in technology come to life almost every day, therefore it is impossible to be knowledgeable on technology and feel confident about it’

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These results, in brief, demonstrate that, although students in this study generally feel comfortable regarding their level of technology knowledge, some do not feel adequate. Knowledge basis from interactions

In this section, students’ knowledge and experiences on PCK, TPK, and TCK are described. Participants’ agreement levels are given in Table A2 (Appendix A). PCK Shulman’s PCK describes developing a new knowledge base using two or more separate knowledge bases as the essence of the best teaching and a foundation of the overall TPACK model, so it is important that preservice teachers be able to use their pedagogic knowledge and content knowledge to develop PCK. The data revealed that although a majority of preservice teachers in this study reported no major problems in the content area, they were not confident about their teaching/ pedagogical experience. Participants’ agreement level also supports this conclusion. About 60% of the participants agreed with the statement given in Table 2 and indicated their inadequacy in pedagogical experience to teach the chosen subject matter. A participant, for example, reported in the project report that, I think that I have adequate knowledge on the subject I chose and ability to teach it in the classroom. Because I know the content well and my teaching approach seems to me an appropriate one. Although this participant seemed to have confidence enough to teach, another student pointed out his own limitations in teaching by stating, I think that I know the subjects [I chose to teach in this project], but I’m skeptical about having enough experience in teaching overall. Being among students and presenting to them, I think, will be helpful to me in increasing my self-efficacy of teaching. Students who reported a lack of pedagogical experience stressed the importance of real classroom teaching experience. One student pointed out that, I think that I know about the topic, but I’m not experienced in teaching because I have not experienced it yet. Another shared that, experience is built up through real activities; I have not experienced such a teaching activity yet. A student’s response to our own conclusion about the data summarizes the response to the issue. She pointed © 2011 Blackwell Publishing Ltd


out that, As long as we don’t know needs and interests of target population [students], I don’t think we can create or develop a pedagogic approach. Therefore, I don’t think having knowledge in the content area would not work by alone. This participant not only shared her thoughts but also pointed out the solution. She noted that, preservice teachers [in our context] need to start teaching practice, going to elementary schools, at the freshman year [currently they go schools for teaching practicum at the senior year]. As they move forward in their classes at the teacher education program, they also develop different pedagogical experience from their teaching practice. As Shulman (1987) discusses in his PCK framework, the need for understanding learners’ interests, needs, difficulties, motivation to learn, and other factors were also highlighted by students in this study. As discussed in many studies, development of PCK is important issue in our study as well. Some of the data categories generated were: lack of teaching experience, learners’ backgrounds, motivation, ability to teach specific content, and need for materials. TPK The TPACK model states that lack of experience or knowledge in one area in the model has resulted in failure or unexpected outcomes. Despite the fact that students in the study had well-grounded technology backgrounds, lack of pedagogical experiences caused very limited use of technology, according to the pedagogical principles they chose. Student projects revealed that use of technology in projects added no new dimensions to their teaching even though they had planned to modify their teaching approach. Participants planned and reported some promising ideas and approaches for technology use, but implementations were not observable in the projects. Shulman (1987) described pedagogy including many types of activities, like subject difficulty, student understanding, questions to ask, assessment approaches, and other components. TPK would thus be the definition of whether or not technology supports teachers in integrating their pedagogic ideas into teaching. Many participants in this study demonstrated use of technology for conveying to learners in a linear fashion and used testing as a major assessment strategy, with a majority (76%) of the participants agreeing to this specific finding. One student’s response to this conclusion © 2011 Blackwell Publishing Ltd

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contributes to understanding of why many agree with it. She pointed out that, I think that the main reason [for the conclusion] originated from the thought that technology itself would be enough to reach to the result or target and push pedagogy aside. Many projects did not reflect learner/teacher interaction, checking points of understanding, and other pedagogic principles described in the overall TPACK model. The students were assumed to have good technology skills but to lack pedagogical experience, so we interpret the data from observation sessions, project reports, and questionnaire reflections to reflect students’ limited use of technology for transforming, supporting, or enriching their pedagogical ideas and for ultimately creating a TPK base. About 83% of the participants expressed conclusion consistent with the findings given in Table 2 and interpretations of their experiences. TCK Data in this section revealed that students were quite capable of creating a TCK base whose essence is to transform content into different forms for presentation to learners. Student projects used various approaches to represent content. For example, some used Flash animation and graphics to teach English words, or used an animated clip to convey the risks of smoking. In addition to the examples of Fig 2, participants were also in favour of using technology to visualize content (92%). However, these efforts were of questionable effectiveness. One participant, for example, developed Flash animations to show static scenes in his project, when he could have effectively conveyed the message with a very simple picture or text with far less expenditure of effort. Therefore, some examples using substantial time and energy to develop different technology products revealed the fact that students in this study were much more focused on technological rather than educational ideas. In other words, some students had no experience or approach for deciding just when and how to most effectively use technology to convey content. About 73% of the students agreed with this conclusion. The overall understanding developed from the data was that the use of technology to distribute content actually requires considering all teaching components together. Without any pedagogical planning, technology cannot be productive or supportive of content transformation. Also, the overall agreement

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Fig 2 Projects developed by preservice teachers.



level in Table A2 (82%, see Appendix A) demonstrates a strong consensus on findings of this study with regard to preservice teachers’ TCK. In addition to representation and visualization of the content using different technologies, appropriateness of the technology and content, planning of technology and content, and effectiveness of the technology for the chosen content were some of the initial categories generated from the data. TPACK Overall, the data indicated that students demonstrated a lack of understanding of technology integration methodology and understanding within the TPACK framework. Lack of both pedagogical experience and understanding of different teaching strategies was a major issue in developing the TPACK knowledge base. Students with technology backgrounds were found to be limited in using technology to teach subject matter of their own choice. Having two core knowledge bases with adequate knowledge (technology and content) leaves only one limitation, lack of PK. Several participants reported a lack of PK or experience with teaching and teaching with technology. A recent study investigating preservice teachers’ development of TPACK has reported similar results in their quantitative analysis (Chai et al. 2010). That study reported that PK had the largest impact on predicting preservice teachers’ TPACK level. Chai et al. (2010) concluded that ‘. . . increasing PK is foundational for developing TPACK. As preservice teachers develop a basic level of PK, they establish a strong knowledge base from which effective technology integration ideas can flourish’ (p. 70). Based on our interpretation of the data, we constructed three major conclusions (findings) and shared them with participants, and Table A2 indicates that approximately 74% of the participants reported a strong consensus with them. One student’s definition of his experience with use of technology in education elegantly summarizes our overall research findings with regard to TPACK. He stresses that, teaching with technology with no pedagogical ideas looks like a fancy present box with no present in it. Although initially, preservice teachers’ PK base seemed to be the only limitation, its impact on other knowledge base creation and creation of the TPACK became major issues. This result supported the TPACK © 2011 Blackwell Publishing Ltd

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model’s overall definition and confirmed that deficiency in one area can result in failure of effective technology use. Understanding the role of technology in teaching and learning, lack of experience in using technology in teaching, pedagogy and technology use, appropriateness of technology and content, limitation of technology, and interaction and technology were some of the categories developed from the data analysis procedure. Discussion

Our study shows that, while students demonstrated a certain level of knowledge in technology, pedagogy, and content, their ability to use knowledge bases and their attempts to create new knowledge bases, like TPK, were limited, principally due to lack of teaching experience. Ozgun-Koca et al. (2010) indicate in their study that preservice teachers’ lack of teaching experience resulted in inability to use technology in teaching. Projects preservice teachers developed in this study were limited in many cases in terms of both transformation of pedagogy and content. Shulman (1987) noted that the knowledge, understanding, and skill expert teachers display with ease were demonstrated ‘haltingly, and occasionally masterfully’ in preservice teachers’ projects in our study. Our findings also indicated that, while the teacher education programme could be effective at conveying theoretical, methodological, and technical knowledge and skills, preservice teachers’ lack of direct teaching experience limit them in effectively using or integrating technology into teaching (So & Kim 2009; Chai et al. 2010). Therefore, results suggest that modeling effective use of technology in teaching throughout the teacher education programme is necessary (Niess et al. 2006). Otherwise, as Bandura (1977) pointed out, technology integration would be ‘exceedingly laborious, not to mention hazardous, if people had to rely solely on the effects of their own actions to inform them what to do’ (p. 22). Therefore, carefully designed case studies or exercises in teacher education programmes could help preservice teachers gain some teaching experience before doing actual teaching in the real classroom. Creating new knowledge bases based on different teaching components is difficult for preservice teachers.

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It requires a deep understanding of the core knowledge basis and interpretation of the teaching context and its dynamics. Developing PCK is an important factor in overall technology integration; teachers must prioritize this before integrating technology. In preservice teacher education, PCK development must be supported with actual teaching experience, so it is necessary to support preservice teachers’ ‘pedagogical reasoning’ development, which refers to the understanding of the process of ‘transforming subject matter into forms that are pedagogically powerful as well as identifying and selecting strategies for representing key ideas in the lesson’ (Shulman 1987; Angeli 2005). Because of PCK development difficulty and the fact that TPACK is based on PCK concept, it would not be theoretically incorrect to note that if one’s PCK development is not fully completed, one would be limited in demonstrating technology use in teaching. The difference between ‘knowing’ and ‘doing’ was also demonstrated in the current study. While ‘knowing’ would be described as having knowledge in pedagogy, content, and technology, ‘doing’ would be a process of implementation of knowledge background into a genuine teaching experience. Although preservice teachers were confident about different knowledge bases, their implementations were limited. Similarly to the results of the study carried out by So and Kim (2009), knowing about technology or the content did not produce effective technology use in the given context. Although preservice teachers may have technology, pedagogy, and content knowledge, TPACK development from interactions among these components was problematic to a certain degree (Marino et al. 2009). The findings of this study indicate that preservice teachers’ lack of teaching experience plays a significant role in their ability to use technology in teaching. Preservice teachers should receive guidance in terms of how to achieve effective technology integration into their teaching. Technology modeling use throughout the curriculum by teacher educators should also be considered as a possibly effective technique. However, the findings of this study strongly suggest that such modeling should not only demonstrate good classroom examples but should also be expanded to include ‘cognitive modeling’ revealing the logic behind the teacher educator’s actions. In addition, instructors could consider developing exercises in which preservice teachers

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see a model of a technology applied to teaching and then try the approach for themselves with limited concepts rather than having an open choice of content to teach. Through such modeling and exercises, shaped with principles of TPACK, preservice teachers would have the opportunity to learn both pedagogical principles (dynamics) and technology selection by an expert. With respect to TPACK structure, the results of this study clearly indicate that, although the theoretical foundations of TPACK have potential to provide insights to educators in terms of integration of technology into teaching and learning activities, this potential is not visible or clearly represented at certain points in Fig 1. The current representation indicates that TPACK knowledge is composed of a combination of different knowledge bases but lacks the procedural steps (i.e. what comes first, next, and last) that must take place in the development process of a TPACK knowledge base. This issue makes it difficult for educators to explain all interactions among knowledge bases. In this study, to overcome this challenge, we followed a processoriented approach defined with theoretical foundations as noted earlier. In this approach, we first examined PCK development, since foundations of TPACK are developed based on the PCK concept, and then move to on other interactions and knowledge bases. In other words, our understanding of the theoretical foundations of TPACK obligates us to follow a hierarchical model (developmental stages by importance) and prioritize PCK development over all other knowledge bases in the data analysis. In the later stages of interpretation of the data, although TPK and TCK were the major knowledge bases with which preservice teachers mostly demonstrated a certain degree of development, we could not, for example, find a direct and strong interaction between TPK and TCK. The only interaction between these two knowledge bases falls in the area of TPACK in the diagram, and it was difficult to differentiate its effect on overall TPACK development. In brief, based on our interpretations of the data and literature, we believe that further studies and research on TPACK should also consider discussing the structure of TPACK and inquire as to whether or not the current TPACK diagram is complete and adequate to represent the full potential of TPACK foundations. The result of this study clearly pointed out that PCK © 2011 Blackwell Publishing Ltd


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development must be prioritized in TPACK development, and this should be explicitly represented in the TPACK diagram. Recommendations

Although the TPACK framework provides educators a useful theoretical landscape to explain how to integrate technology into teaching, implementation of those principles is not an easy task. Preservice teachers in our study struggled with development of new knowledge bases. Creation of new knowledge bases from interactions among core components was one of the major points found to be challenging and complex. Our conclusion is to suggest further research study, continuing investigation of the process of knowledge bases creation (i.e. TPK, PCK, TPACK) from interactions among different components of the overall framework. This would provide useful insights for understanding the limitations, challenges, and dynamics of the components and their development, and provide useful

ideas to be implemented in teacher education programmes. Also, participants in the current study had good technical backgrounds but limited or no pedagogical experience. Therefore, research with different participant backgrounds (i.e. preservice teachers and teachers with pedagogical experience or limited technical background) in a different context would certainly enlighten us on the creation of new knowledge bases. Further research with different participant backgrounds would probably provide us some useful insight whether pedagogical experience remains the major barrier developing TPACK knowledge base, or how participants who are limited in both technology and pedagogy prioritize their limitations. Acknowledgements

The author thanks Dr. Ali Eraslan from Ondokuz Mayis University, and the anonymous reviewers and the editor for their constructive feedback.

Appendix A Table A1. Participants’ agreement level to findings (content, pedagogy, and technology). Knowledge base

Average number of responses for each finding

Number of findings (from Table 2)

Average agreement level

Content knowledge

49

1

Pedagogical knowledge

48

4

Technological knowledge

49

1

Agree: 90% (44) Neutral: 2% (1) Disagree: 8% (4) Agree: 69% (33) Neutral: 15% (7) Disagree: 16% (8) Agree: 61% (30) Neutral: 14% (7) Disagree: 25% (12)


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Table A2. Participants’ agreement level to findings (PCK, TPK, TCK, and TPACK). Knowledge base

Average number of responses for each finding

Number of findings (from Table 2)

Average agreement level/# of participants

PCK

48

1

TPK

49

2

TCK

48

2

TPACK

49

3

Agree: 86% (44) Neutral: 8% (1) Disagree: 4% (4) Agree: 83% (40) Neutral: 13% (7) Disagree: 4% (2) Agree: 82% (40) Neutral: 9% (5) Disagree: 8% (4) Agree: 74% (36) Neutral: 21% (10) Disagree: 5% (3)

PCK, pedagogical content knowledge; TCK, technological content knowledge; TPACK, technological pedagogical content knowledge.

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