April 2012 Volume 15 Number 2 - Educational Technology & Society

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Braxton, J. M., & Lien, L. A. (2000). The viability of academic integration as a central construct in Tinto's interactionalist theory of student departure. In J. M. Braxton (Ed.), Reworking the student departure puzzle (pp. 11-28). Nashville: Vanderbilt University Press. Clifton, D. O., & Anderson, E. C. (2002). StrengthsQuest: Discover and develop your strengths in academics, career, and beyond. Washington, DC: The Gallup Organization. Fuller, D., Norby, R. F., Pearce, K., & Strand, S. (2000). Internet teaching by style: Profiling the on-line professor. Journal of Educational Technology and Society, 3(2), 72-85. Hagedorn, L. S. (2000). What contributes to job satisfaction among faculty and staff: New directions for institutional research. San Francisco: Jossey-Bass. Heuer, R., Kuhr, B., Fahimi, M., Curtin, T. R., Hinsdale, M., & Carley-Baxter, L. (2005). 2004 National study of postsecondary faculty (NSOPF:04) methodology report (NCES 2006-179). Washington, DC: Department of Education. Katzell, R. A., Thompson, D. E., & Guzzo, R. A. (1992). How job satisfaction and job performance are and are not linked. In C. J. Cranny, P. C. Smith, & E. F. Stone (Ed.), Job satisfaction (pp. 195-217). New York: Lexington. Kerr, M. S., Rynearson, K., & Kerr, M. C. (2006). Student characteristics for online learning success. Internet and Higher Education, 9(2), 91-105. Kolb, D. A. (1984). Experiential Learning: Experience as the source of learning and development. Englewood Cliffs: Prentice Hall, Inc. Maslow, A. H. (1954). Motivation and personality. New York: Harper & Brothers. Pollicino, E. A. (1996, April). Faculty satisfaction with institutional support as a complex concept: Collegiality, workload, autonomy. Paper presented at the Annual Meeting of the American Educational Research Association, New York, NY. Retrieved from ERIC database. (ED394428) Readiness for Education at a Distance Indicator. (2009). Retrieved March 21, 2009, from http://www.readi.info Rosser, V. J., & Townsend, B. K. (2006). Determining public 2-year college faculty's intent to leave: An empirical model. Journal of Higher Education, 77(1), 124-147. Smarter Measure Learning Readiness Indicator. (2010). Student Readiness Report. Retrieved March 1, 2011, from http://www.smartermeasure.com/documents/2010_Online_Student_Readiness_Report.pdf Veronica, M., & Lawrence, M. (1997). Secondary school teachers and learning style preferences. Educational Psychology, 17(1- 2), 157-170. Vroom, V. H. (1964). Work and motivation. New York: Wiley. 353
Hsu, Y.-C., Ho, H. N. J., Tsai, C.-C., Hwang, G.-J., Chu, H.-C., Wang, C.-Y., & Chen, N.-S. (2012). Research Trends in Technology-based Learning from 2000 to 2009: A content Analysis of Publications in Selected Journals. Educational Technology & Society, 15 (2), 354–370. Research Trends in Technology-based Learning from 2000 to 2009: A content Analysis of Publications in Selected Journals Yu-Chen Hsu 1 , Hsin Ning Jessie Ho 1* , Chin-Chung Tsai 1 , Gwo-Jen Hwang 1 , Hui-Chun Chu 2 , Chin-Yeh Wang 3 and Nian-Shing Chen 4 1 Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan, #43, Sec. 4, Keelung Rd., Taipei, 106, Taiwan // 2 Department of Computer Science and Information Management, Soochow University, 56 Kueiyang Street, Section 1, Taipei, Taiwan 100, R.O.C. // 3 Research Center for Science and Technology for Learning, National Central University, No.300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan R.O.C. // 4 Department of Information Management, National Sun Yat-sen University, No. 70, Lien Hai Rd., Kaohsiung, Taiwan, 80424, R.O.C. // hsuyuchen@mail.ntust.edu.tw // hojessie@gmail.com // cctsai@mail.ntust.edu.tw // gjhwang.academic@gmail.com // carolhcchu@gmail.com // chinyeawang@gmail.com // nschen@mis.nsysu.edu.tw *Corresponding author (Submitted April 18, 2011; Revised June 5, 2011; Accepted July 12, 2011) ABSTRACT This paper provides a content analysis of studies in technology-based learning (TBL) that were published in five Social Sciences Citation Index (SSCI) journals (i.e. the British Journal of Educational Technology, Computers & Education, Educational Technology Research & Development, Educational Technology & Society, the Journal of Computer Assisted Learning) from 2000 to 2009. A total of 2,976 articles were cross-analyzed by three categories including research topic, research sample group, and learning domain. It was found that “Pedagogical design and theories” was the most popular research topic, “Higher Education” was the most utilized sample group, and “Non-specified” and “Engineering/Computer sciences” were the most selected learning domains in the last decade. However, topics in “Motivation, Perceptions and Attitudes” drew more attention in the latest five years, while the number of articles in “Digital game and intelligent toy enhanced learning” and “Mobile and Ubiquitous Learning” grew significantly between 2005 and 2009. Furthermore, the Chi-square analysis results showed that there were significant associations among these three categories. The results of the analysis provide insights for educators and researchers into research trends and patterns of technology-based learning. Keywords Research trends, Technology-based learning, Content analysis Introduction Technology-based learning is increasingly important in the 21 st century. However, studies in analyzing its appropriateness, its application and practices, and its influence on today’s education are still under debate and discussions (e.g. Chan, Hue, Chou, & Tzeng, 2001; Shih, Feng, & Tsai, 2008). Besides, numerous studies in this area have explored a wide range of topics, such as the improvement in technology-based learning environments, the effectiveness of web-based instruction, and the integration of new technology into classrooms. Therefore, reviewing the research trend of technology-based learning may help the researchers in related fields to identify their research interests and design considerations. Besides, the study will also provide policymakers with a reference to make plans in the future. Hence, it is important and meaningful to examine the technology-based learning research trends at this point. This study intends to investigate the research trends of technology-based learning from 2000 to 2009. Five major research journals were selected for analysis, namely the British Journal of Educational Technology (BJET), Computers and Education (C&E), Educational Technology Research & Development (ETR&D), Educational Technology & Society (ET&S), and the Journal of Computer Assisted Learning (JCAL). The research questions addressed by this paper include: 1. What research topics related to technology-based learning were published in these selected journals from 2000 to ISSN 1436-4522 (online) and 1176-3647 (print). © International Forum of Educational Technology & Society (IFETS). The authors and the forum jointly retain the copyright of the articles. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear the full citation on the first page. Copyrights for components of this work owned by others than IFETS must be honoured. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from the editors at kinshuk@ieee.org. 354
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April 2012 Volume 15 Number 2
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Supporting Organizations Centre for
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Contextualizing a MALL: Practice De
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Kop, R. (2012). The Unexpected Conn
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Human mediation and information flo
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elevant information based on some k
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of learners. A search facilitated t
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information as human mediation mean
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Blau, I., & Barak, A. (2012). How D
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examined whether the readiness to p
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Table 5 presents the ANOVA for the
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However, in discussing a non-sensit
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deviations showed smaller variance,
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actual participation discussing sen
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Mesch, G., & Elgali, Z. (2009). Soc
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Although prior research on overall
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with a score of 39 and below as “
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Table 2 demonstrates mean scores an
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Discussion Although the recent Inte
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Furthermore, the most preferred pla
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MEB. (2009). Internete erisim proje
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Learning Management Systems (LMS) b
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practice and repetition with feedba
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Online peer assessment Peer assessm
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At an international conference on m
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� Ability to produce rich assessm
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Meishar-Tal, H., & Tal-Elhasid, E.
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Tsai, S. C. (2012). Integration of
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order to decrease text complexity a
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matter how the learners’ aptitude
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If compared by programs, WP student
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mean F2F 4.64 4.52 4.35 4.44 *: p
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een analyzed and were compared with
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Chen, G.-D., Lee, J.-H., Wang, C.-Y
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and diverse cognitional and emotion
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Encourage and persuade students wit
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Materials and procedure Each studen
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The lower part of Figure 4 shows st
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Mayer, R. E., Sobko, K., & Mautone,
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that an item is answered correctly
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Table 1. Relative concepts frequenc
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The Account Management Module provi
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Experiment 1 and results Figure 7.
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Utilization of Test Item 36 33 30 2
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Utilization of Test Item 36 33 30 2
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0.065 0.877 (17.56) 0.938 (22.55) 0
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Hwang, G.J., Hsiao, C.L., & Tseng,
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the diverse needs of modern industr
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Figure 1. The framework of interdis
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Research Design Figure 3. Recommend
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friendly. 8. I feel the layout and
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satisfaction, and system acceptance
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Ozok, A. A., Fan, Q., & Norcio, A.
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than students in a conventional cla
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shown in Figure 2 to include the st
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(1996) Pleasure-Arousal-Dominance (
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Based on this connection, we consid
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Final dominance measurements were p
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student mood and thereby allow comp
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Sessink, O., Beeftink, H., Tramper,
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The rationale behind the video form
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usefulness of the movies and their
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case of the first two questions and
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this paper in order to evaluate the
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The survey questions Appendix A In
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E-training in organizations E-train
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efficacy regarding online training,
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Method Sample and procedure Figure
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0.874 which exceeded the recommende
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Even though the result does not con
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Brown, M., & Cudeck, R. (1993). Alt
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Wen, Y., Looi, C.-K., & Chen, W. (2
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when they are designing and impleme
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paper focuses on the first three st
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their self-esteem to be partners in
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Democratizing knowledge and symmetr
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1) Reading the article: At the star
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Effects of RCKI principle-based ped
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References Alexander, C. (1979). Th
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Valsamidis, S., Kontogiannis, S., K
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The Analog system (Yan et al., 1996
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First, the number of the sessions a
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BioLayout uses a modified version o
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As shown in figure 3, all metrics c
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Figure 7. The detailed results for
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Enright, A. J., van Dongen, S., Ouz
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Chu, S. K. W., Kwan, A. C. M., & Wa
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teachers, as well as collaboration
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from the students’ ratings appear
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Table 5 summarizes the students’
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eading blogs (i.e., reminders, easy
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Luehmann, A. L. (2008). Using blogg
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Uzunboylu et al. (2009) examined th
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System implementation Overview of M
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Methods Before the experiment, a mo
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too simple, incomplete, or they eve
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Comparisons of UMLS Questionnaire i
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already described may play an impor
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Parker, D., Manstead, A. S. R., Str
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Avci, U., & Askar, P. (2012). The C
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Literature review The related varia
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collected through Personal Informat
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Self-efficacy 92 5 21 13.37 3.726 W
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In this problem, intention was take
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References Ajjan, H., & Hartshorne,
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Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
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Students perused the course materia
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problem. All articles were then sen
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tests, electronic tests are more li
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Students 10 and 11: My classmate Ed
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collection was also approved by all
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Ubiquitous Revision Seamless Collab
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Tai, Y. (2012). Contextualizing a M
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tasks were developed from task type
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experiences in this phase. Moreover
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test is administered again right af
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The collected data were analyzed wi
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Gorp, K. V., & Bogaert, N. (2006).
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4PL IRT model According to the numb
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examinee’s ability more accuratel
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would be more accurate if items j+1
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C�I or Change I�I) would be 0.2
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improved by rearrangement procedure
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Table 6. Repeated Measures ANOVA of
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Leppisaari, I., & Lee, O. (2012). M
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Selection of the virtual tool The t
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Environmental themes emerged strong
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Visualization of text (visual langu
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environments where visual technolog
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- Logging in to learning environmen
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McNaught, C., Lam, P. & Lam, S.L. (
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on-site to finally achieve a meanin
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Table 1. Digital game designers and
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worldviews are socio-cultural-histo
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Phase Methods Visitor data collecti
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operate the game without the help o
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Visitors (end users) must be heard.
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Islas Sedano, C., Pawlowski, J., Su
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part of something larger than the s
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Previous studies have developed rel
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Technology Acceptance. The 10 items
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Table 4. Model Fit Indices Model χ
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In the final path model of set 1, t
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Discussion Differing from prior stu
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Haythornthwaite, C., Kazmer, M. M.,
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Ge, Z.-G. (2012). Cyber Asynchronou
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college of a university situated in
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Table 3 shows us the following info
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Appendix B shows Class 1’s respon
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increase one’s ability to process
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Appendix A Responses concerning syn
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Shih, S.-C., Kuo, B.-C., & Liu, Y.-
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Adaptive U-learning Math Path Syste
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