January 2012 Volume 15 Number 1 - Educational Technology ...

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Poole, D. M. (2000). Student participation in a discussion-oriented online course: A case study. Journal of Research on Computing in Education, 33(2), 162–177. Pryor (1994, April). Family-school bonding and student success. Paper presented at the 75th annual meeting of the American Educational Research Association, New Orleans, LA. Rencher, A. C. (2002). Methods of Multivariate Analysis. New York: John Wiley & Sons. Swan, K. (2002). Building learning communities in online courses: The importance of interaction. Education Communication and Information, 2(1), 23–49. Trinidad, D. R., & Johnson, C. A. (2002). The association between emotional intelligence and early adolescent tobacco and alcohol use. Personality and Individual Differences, 32(1), 95–105. Vrasidas, C., & McIsaac, M. S. (1999). Factors influencing interaction in an online course. American Journal of Distance Education, 13(3), 22–36. Wagner, E. D. (1994). In support of a functional definition of interaction. American Journal of Distance Education, 8(2), 6–29. Wang, A. Y., & Tucker, T. L. (2001). A discourse analysis of online classroom chats: Predictors of cyber-student performance. Teaching of Psychology, 28(3), 222–226. Wang C., & Reeves T. C. (2007). The meaning of culture in online education: implications for teaching, learning, and design. In A. Edmundson (Ed.), Globalized E-Learning Cultural Challenges. Hershey, PA: Information Science Publishing. Wehlage, G. G., Rutter, R. A., Smith, G. A., Lesko, N., & Fernandez, R.R. (1989). Reducing the Risk: Schools as Communities of Support. Philadelphia: Falmer Press. Yoon, S. (2006). Two group development patterns of virtual learning teams: Linear progression and adaptive progression. The Quarterly Review of Distance Education, 7(3), 297–312. Zins, J. E., Weissberg, R. P., Wang, M. C., & Walberg. H. J. (2004). Building academic success on social and emotional learning: What does the research say? New York: Teachers College Press. 89
Shih, W.-C., Tseng, S.-S., Yang, C.-C., Lin, C.-Y., & Liang, T. (2012). A Folksonomy-based Guidance Mechanism for Contextaware Ubiquitous Learning: A Case Study of Chinese Scenic Poetry Appreciation Activities. Educational Technology & Society, 15 (1), 90–101. A Folksonomy-based Guidance Mechanism for Context-aware Ubiquitous Learning: A Case Study of Chinese Scenic Poetry Appreciation Activities Wen-Chung Shih, Shian-Shyong Tseng * , Che-Ching Yang 1 , Chih-Yu Lin and Tyne Liang 1 Department of Applied Informatics and Multimedia, Asia University, Taichung, 41354, Taiwan (R.O.C.) // 1 Department of Computer Science, National Chiao Tung University, Hsinchu, 30010, Taiwan (R.O.C.) // sstseng@asia.edu.tw *Corresponding author ABSTRACT In this work ubiquitous learning technologies are applied to Chinese scenic poetry appreciation. A folksonomybased approach is proposed to accumulate knowledge about poems and their corresponding scenic spots. A user can use a “Tagging” operation by a smart phone to associate a concept (a word, a phrase or a sentence) with a scenic spot. These associations will be recorded in a folksonomy, which is then transformed into a Learning Guidance Tree to support personalized guidance in u-learning environments. The purpose of this work is to propose a folksonomy-based guidance mechanism. Also, we attempt to find students’ and teachers’ attitudes towards the innovative application through a case study. To show the effectiveness of the innovative approach, a ubiquitous learning system was developed to conduct Chinese scenic poetry appreciation activities for a fifthgrade Chinese course in Taiwan, in which forty-eight students participated. The survey results show that the system had a positive impact on students’ learning, especially on the affective domain including participation, motivation and interaction. Keywords Chinese scenic poetry, Ubiquitous learning, Folksonomy, Context-aware, Tagging Introduction In recent years context-aware ubiquitous learning (u-learning) has become a hot research topic (Chiou et al., 2010; Chu et al., 2010; Hwang, Kuo et al., 2010; Hwang, Tsai et al., 2008; Hwang et al., 2009; Yang, 2006). In contextaware ubiquitous learning environments, students’ learning behaviors can be detected by sensors embedded in realworld resources. Thus, learning systems can provide students with adaptive learning support. In spite of its benefits, context-aware ubiquitous learning has been primarily applied to the instruction of subjects with well-structured knowledge and subjects whose knowledge is mostly defined with correct answers, such as natural science, science experiments and language training. For example, digital guidance can be provided for pupils to observe and classify real-world plants and insects in ubiquitous learning activities (Hwang, Chu et al., 2010). The main reason for this is that existing approaches to acquiring knowledge of such subjects can be adopted for learning guidance. Repertory grids, decision trees and knowledge engineering approaches have been proposed to construct knowledge bases for learning guidance (Chu et al., 2010; Hwang, Chu et al., 2010). This study extends the application of ubiquitous learning to subjects which are aimed to train students to be creative and imaginative, beyond the cognitive skills of memorization and comprehension. Chinese scenic poems describe scenery in high-level ancient Chinese and express profound concepts by implication, which are difficult for children without related experiences to understand. Our idea is to use a ubiquitous learning environment to guide students to construct experience related to the poems. In this paper a folksonomy-based approach is proposed to record, accumulate, organize and share students’ feelings related to poems while learning Chinese poetry outdoors. Then, folksonomy-based knowledge can be used to guide students in learning Chinese poetry. A folksonomy is a user-generated taxonomy employed to categorize and retrieve web content such as Web pages, photographs and Web links using user-defined labels called tags (Jaschke et al., 2008; Tsui et al., 2010). Typically, a folksonomy has a flat structure consisting of several user-defined categories. In essence, the tags are organized according to poems and locations. Also, what the students see, do and feel is recorded in the folksonomy. By making use of GPS-enabled (Global Positioning Systems) smart phones, the student’s location can be recorded by the backend server and thus, while learning Chinese poetry outdoors, students can receive appropriate recommendations and guidance which will enhance their learning experience and learning activities. In addition, students can express the intended concepts learned from the poems by providing text tags or/and photographs. 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. 90
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January 2012 Volume 15 Number 1
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Supporting Organizations Centre for
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Analyzing the Learning Process of a
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Angeli, C., & Valanides, N. (2012).
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ased on an integration and evaluati
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ased on the assumption that no sing
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Diagram type D thinking (shown in F
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collaborative task in terms of inte
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Table 4. Descriptive statistics for
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Hong, N. S., Jonassen, D. H., & McG
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commercial off-the-shelf digital ga
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The post-questionnaire was used aft
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Phase Table 1. Phases and activitie
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Research results Describing student
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Assessment results for each one of
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References Annetta, L.A., Minogue,
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Huang, T.-W. (2012). Aberrance Dete
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Detection power Typically, the rela
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Results Detection rates As seen in
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2 .00 .05 3 .02 .10 1 .60 .40 ECI 4
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their easily understandable devices
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Page 91 and 92: Literature in the field of online l
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Page 105 and 106: References Abowd, G. D., & Atkeson,
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Page 109 and 110: Figure 1. The five stages of KT (Gi
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Page 115 and 116: Figure 3. Canonical structure betwe
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Page 119 and 120: Langan-Fox, J., Platania-Phung, C.,
Page 121 and 122: Gömleksiz, M. N. (2012). Elementar
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Page 127 and 128: conditions of a learning environmen
Page 129 and 130: Kahle, J. B. (1983). The disadvanta
Page 131 and 132: Appendix A Science and Technology S
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Page 135 and 136: Questionnaire on student satisfacti
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Figure 1 illustrates how the abovem
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teacher/instructor continues to dom
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The instructor plays a significant
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Data collection and data sources Fi
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y turning over the responsibility t
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Brophy, J. (1999). Toward a model o
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Lawanto, O., Santoso, H. B., & Liu,
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such as grades and evaluation by ot
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students’ interest, expectancy fo
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constructs that measure students’
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Bandura, A. (1978). Reflections on
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Lin, J. M.-C., & Liu, S.-F. (2012).
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Table 1. The MSWLogo commands learn
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other words, we had prepared a set
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lab. When she returned and found th
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Attitudes toward Programming and Co
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Table 5 successfully, it took four
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Kuter, S., Altinay Gazi, Z., & Alti
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not only the means for trainees’
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Data Collection Techniques and Anal
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organizations was highlighted by on
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provides the means for professional
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Kohonen, V. (2001). Towards experie
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As Rogers (1995) postulates in his
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Instrument and data collection Afte
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“Raising our computer skills in C
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teachers deploy ICT tools in langua
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Ma, W., Anderson, R., & Streith, K.
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APPENDIX A. Questionnaire for Dista
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consistency with other ideas, and a
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conceptions, justifying their belie
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each group. The experimental group
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specifically, instructional approac
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Table 3 shows that the mean frequen
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previous Web-based instructional le
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Millar, R., & Osborne, J.F. (1998).
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Several studies explore the roles t
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understand the content structures o
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teacher was not allowed to provide
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two coding schemes, as illustrated
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also very limited. Teachers and sof
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learning activities. British Journa
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2009; Bernard & Cathryn, 2006) or p
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In this study, the focus of the ins
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The student’s degree of mastery i
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The questionnaire for the acceptanc
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the t-test result, it is found that
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Scale Questionnaire item Mean S.D.
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Hwang, G. J. (2003). A conceptual m
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sharing, problem solving, and achie
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Virtual learning environment In the
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Class Table 1. The survey questions
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“…the distance and the lack of
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collaboration within EVS, thus prev
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Huang, T.-H., Liu, Y.-C., & Chang,
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y personalised context examples in
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Students’ Problem-Solving Guidanc
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Research Method Figure 8. The scree
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Table 4. Abstract of Pairwise Compa
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questions designed for the system h
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Lee, J. (2012). Patterns of Interac
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This study focused on online fora i
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Results and Discussion Due date-cen
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In addition, all groups developed 8
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future. Therefore, they had an oppo
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surprising that most interaction wa
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Pawan, F., Paulus, T. M., Yalcin, S
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systems by using 18 personalization
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Short-Term Sensory Memory is a temp
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with respect to articles by using a
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system also computes a review value
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DFL. d ( yi ) is the degree of mem
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the experimental group can understa
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Finally, Figure 10(A) and Figure 10
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Appendix # Question Description Par
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mental models, are cognitive struct
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Based on the theoretical implicatio
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Data analysis To test the model fit
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may be considered an effective inte
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Hsu, I.-C. (2012). Intelligent Disc
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(Gradinarova, Zhelezov et al. 2006)
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RLO denotes a remote learning objec
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Figure 2. The flow-oriented LOFinde
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if x include with y, and y include
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Similarly, the relation metadata of
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(defrule student-advisor (triple (p
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References ADL. (2006). Sharable Co
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determinants of how people think, b
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Mediating effect of learning flow A
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The instrument used to measure lear
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addition, the cross-loadings of the
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and ease of use had significant eff
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Connell, J. P., Spencer, M. B., & A
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Despotović-Zrakić, M., Marković,
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Learning is a cognitive activity th
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The survey consisted of 30 question
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Created data mining model needs to
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dealt with the matter taught at the
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Conclusion Conducted research showe
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Romero, C., Ventura S., García E.,
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prompts as scaffolding strategy to
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Reflection Types This study attempt
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All the three groups completed the
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Results Learning Outcomes Pre- and
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Map Analysis in Transfer Test Figur
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Generic Prompts and Specific Prompt
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Biswas, G., Schwartz, D., Bransford
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Chen, Y.-H., Looi, C.-K., Lin, C.-P
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of correct response, answer until c
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Figure 7 shows a screenshot of one
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Collaboration Questionnaire results
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following diagrams. The double-arro
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“Most students were encouraged to
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Bangert-Drowns, R.L., Kulick, C. C.
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primary research questions. First,
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Individual learning Figure 2. Scree
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Experimental Tools This study emplo
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Table 3 shows that almost all items
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I usually engaged myself in listeni
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References Bloom, B. S. (Ed.). (195
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APPENDIX 2. Taxonomy for Informatio
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understand how we can effectively u
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5. Is there a relationship between
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correlation between teachers’ IWB
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Q7. IWB provides advantages to me t
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training regarding this topic. This
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Conclusion This study provides a so
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Smith, H. J., Higgins, S., Wall, K.
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