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Context-based resource retrieval phase The purpose of this system is to support situated poetry learning under a teacher’s guidance. In addition, this system can also support individual learning. For group learning, a teacher uses the user interface to set presentation poems before starting the class and then students learn the prepared poems. For individual learning, students can learn any poem by using the function of poem recommendation. To assist students with identifying their intentions about user context, we propose a context-based dialogue approach to interact with students. The context-based dialogue for intention finding includes two parts: poem recommendation and multimedia resource retrieval. In terms of poem recommendation, PMRI ontology traversal approach (e.g., listing a specific term's hyponyms) is provided to interact with users to find their intentions regarding the dramatic situations of poems. For reducing the options during dialogue, a higher usage concept heuristic is used as below. Example 1 shows an example of the dialogue process for poems. Heuristic of higher usage concept A higher usage concept denotes a concept used frequently in the poems, which can be used to guide students to select suitable keywords as their intentions. If the np of the concept node in PMRI is higher than the threshold, the concept will become one of the options during dialogue. Example 1: Dialogue process for poems This example illustrates the dialogue about a student’s intentions for poems. Q: Which subject do you want to describe (people, human affairs, or substance)? A: People. Q: Which about people interests you (identity, relation, or career)? A: Relation. Q: Which subject within “relation” interests you (friend, classmate, or master)? A: Friend. Q: Which subject within “friend” interests you (intimate, acquaintance, or old friend)? A: Old friend. To gauge the similarities between the student’s intentions and the poems, this study uses the cosine function, used to measure common similarities. The following defines the similarity comparison. VA •VB Similarity = cosine( VA, VB ) = | VA || VB | VA and VB are the keyword vectors, which represent the student’s intentions and the poem’s representative, respectively. The larger the value is, the more similar the two vectors are. In terms of multimedia resource retrieval, individual student can set his/her tolerance degree regarding speed of resource presence, degree of availability, and degree of trust in advance. Then, if these values of ROs fit in with the values of students’ preference (e.g., response time of RO is smaller than acceptable due time, TResponse < TDue), the different types of ROs are ranked and presented based on trust. The definition of response time and bandwidth is defined below. Example 2 shows an example of the dialogue process for ROs. Example 3 shows an example of multimedia resource retrieval. Definition of Response time: This study applies response time to evaluate the length of time a Web site will take to present a resource based on its file size and bandwidth. TResponse = FileSize Bandwidth Definition of Bandwidth: Bandwidth is a data transfer rate for the amount of data that can be carried from one point to another in a given 287
time period. Bandwidth is measured in bits (of data) per second (bps). FixedFileS ize Bandwidth= Transferti me Example 2: Dialogue process for resources This example illustrates the dialogue about a student’s intentions for multimedia resources. Q: What kinds of resource types do you prefer (image, audio, video)? A: image, video. Q: Please set the value of availability. (Default: 1) A: 1. Q: Please set the value of trust. (Default: 1) A: 1. Q: Please set the value of due time. (Default: 1 min) A: 1. Example 3: Multimedia resource retrieval Figure 4. Multimedia resource retrieval for Yellow Crane Tower As Example 1 shows, the intention is “old friend.” The overall intentions of the student are: “old friend, farewell, river, and sad.” Then, this system computes the similarity degree between the learner’s intentions and keyword set of poems and recommends several poems, such as Seeing Meng Hao-Ran off to Guangling at Yellow Crane Tower (Poet: Li Bai), A farewell to a friend (Poet: Li Bai), and Farewell (Poet: Wang Wei). Ultimately, the student chooses to learn Seeing Meng Hao-Ran off to Guangling at Yellow Crane Tower and then multimedia resources related to this poem are pre-selected. As shown in Example 2, the student’s intentions of multimedia resource are acquired and then some of the pre-selected multimedia resources will be filtered. Figure 4 shows a snapshot of the retrieval of the appropriate multimedia resources based on the student’s intentions. Experiment and analysis The UPLS was implemented on a Microsoft Windows Mobile Operating System (OS) platform and JSP Web application. The UPLS contains a user model and an activity model (Griffiths et al., 1998). The user model is used to store the features of users, which includes user profile and group user profile. Regarding the activity model, it is used to provide learning activity for learners, and collect learners’ access data. 288
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http://www.ifets.info ISSN: 1436-45
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Supporting Organizations Centre for
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Timely Diagnostic Feedback for Data
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Lim et al. addressed two gaps, a us
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The new found benefits of technolog
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analysis of all articles submitted
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Since some articles could not meet
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Table 2. Distribution of research t
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Research method Table 8 shows diffe
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authors concluded that mixed-method
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trends. Library and Information Sci
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Taylor, E. W. (2001). Adult Educati
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Zealand 10 paper 15 19 Using mutual
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impact on a variety of sectors arou
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Grand challenges These grand challe
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eport for details of competencies c
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learning repositories to use in con
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Acknowledgements This paper is base
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eliminating duplicates, a total of
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Findings of this review In the foll
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Table 2. Summary of empirical resea
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students’ conception of learning
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their creative capacity in designin
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which make it impossible to see how
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The content knowledge Table 3 depic
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The first revision we have made to
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Angeli, C., & Valanides, N. (2005).
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Lee, H., & Hollebrands, K. (2008).
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Rushby, N. (2013). The Future of Le
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The top ten in the 2011 survey were
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My first vision of the future is on
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References Dienstag, J. (2006). Pes
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industries, new laws, and new areas
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or distractive effects of technolog
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This may be further complicated by
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espect, the literature about school
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Tondeur, J., Van Keer, H., van Braa
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Disruptive technology When mainfram
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with the physical environment, such
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mockups, and then embedded in compu
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the global marketplace. Students in
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games, and virtual worlds are domin
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Malone, T. W. & Lepper, M. R. (1987
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education reform. In the following
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error elimination and/or refutation
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In essence, as depicted in figure 1
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of our students, who are the future
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Simon, H. (1996). The Sciences of t
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2010). Similar patterns can be obse
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To complement the literature search
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Figure 1. Domains of sustainable e-
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Discussion and conclusions This sco
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Baty, P. (2010, July 1). Global rep
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Loewenberger, P., & Bull, J. (2003)
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applied query expansion techniques
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di, 1 ≤ i ≤ n , 0 < d i ≤ 1,
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Procedure Figure 2 schematically de
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Phase 3. Wiki-based revision Throug
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Table 4. Comparison of the performa
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materials manually by working alone
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# Question 1 2 3 4 5 Table 7. Users
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Kuo, Y. H., & Huang, Y. M. (2009).
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Nevertheless, one of the major prob
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Rlj indicates the answer of the l t
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Relative weight Very low 5 ww , ∈
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Experiment and evaluation Figure 7.
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and CG (59.06 and 13.52). The resul
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Expert 1 Expert 2 Expert 3 Correctn
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The EFWA algorithm Appendix Defini
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y the fourth student correctly is:
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drA = − + − + − = 2 2 2 ( , M
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students have achieved what they wa
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environments. This gap can be bridg
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can understand, as well as a vehicl
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5. “Then move on to Loop 2.” Ea
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fact that the students could not ge
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conceptualization, and testing in n
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Soloway, E., Norris, C., Blumenfeld
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all image search queries result in
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instance, not knowing how to naviga
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displays in real time. The authors
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Significance was not found for main
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manifestation of visual literacy; a
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Mayer, R. E. (2001). Multimedia lea
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McMillen (1996) considered virtual
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Learning of area concepts in elemen
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shrink. changed. Hints and Show but
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Based on teacher observations and c
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Appendix 1. Sample items of BACT *I
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Wong, L.-H., Hsu, C.-K., Sun, J., &
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Johnson and Johnson (1994) identifi
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Design of game-based learning activ
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Findings The students exhibited hig
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We take two instances of character
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In designing Chinese-PP, we instead
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Boticki, I., Looi, C.-K., & Wong, L
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Hwang, G.-J., Sung, H.-Y., Hung, C.
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2000). For example, Filippidis and
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amount of information about the lea
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The factors that affected the stude
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Burguillo, J. C. (2010). Using game
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Wong, L.-H. (2013). Analysis of Stu
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Recognizing both the importance and
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Student responses were coded based
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English with the translations of th
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With her mother’s support, Jane w
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LGC that could occur in any physica
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The significance of the reported st
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Chen, Y.-L., Pan, P.-R., Sung, Y.-T
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them develop new concepts to facili
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Figure 1. Visualization of how mino
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experimental group all the other le
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Procedures All subjects in both gro
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misconceptions corrected by a learn
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exploration environment constructed
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Küçüközer, H., & Kocakülah, S.
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Lin, J.-W., Lai, Y.-C., & Chuang, Y
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The related works Feedback should b
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E 2 1 R 23 N E 5 R 15 E 1 R 13 E 3
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Once the frequent itemsets have bee
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Page 243 and 244: To assure pretest validity and reli
Page 245 and 246: Questionnaire and interviews To und
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Page 249 and 250: According to Angeli and Valanides (
Page 251 and 252: description, objectives, and entry
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Page 257 and 258: eing aware of the importance of sel
Page 259 and 260: References Airasian, P. W., & Walsh
Page 261 and 262: Instructional Technology Instructio
Page 263 and 264: and He (2006) revealed that technol
Page 265 and 266: Model and hypothesis development Sa
Page 267 and 268: Table 1. Student profile Gender: Ma
Page 269 and 270: H3 Student satisfaction has positiv
Page 271 and 272: Conclusions Addressing four PRS iss
Page 273 and 274: Tao, Y.-H., & Yeh, R. C. (2009, Jul
Page 275 and 276: My overall experience of PRS is abs
Page 277 and 278: skills can move to the next learnin
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Page 281 and 282: illustrates the Monopoly gameplay m
Page 283 and 284: Comparison of monopoly and instruct
Page 285 and 286: Guskey, T. R., & Gates, S. L. (1986
Page 287 and 288: Yang, C.-C., Tseng, S.-S., Liao, A.
Page 289 and 290: text only because learners are able
Page 291: Figure 2. Structure of poetry multi
Page 295 and 296: Participants and experimental proce
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Page 301 and 302: Wang, Y.-H., Young, S. S.-C., & Jan
Page 303 and 304: mistakes in front of the teacher an
Page 305 and 306: Basic English learning materials we
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Page 309 and 310: H.L, M = 38.11) which occurred in b
Page 311 and 312: Discussions Tangible learning compa
Page 313 and 314: We can conclude from the current st
Page 315 and 316: Joo, Y. J., Joung, S., & Kim, E. K.
Page 317 and 318: on 506 students registered for cybe
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Page 323 and 324: Structural model examination Table
Page 325 and 326: Direct effect Flow ← Satisfaction
Page 327 and 328: Second, the results of this study c
Page 329 and 330: Kim, H. S. (2008). The effects of t
Page 331 and 332: language accurately, or product-ori
Page 333 and 334: Thailand 5 Vietnam 25 Total 208 Res
Page 335 and 336: Procedures of data collection Figur
Page 337 and 338: discussions. From Brian’s log fil
Page 339 and 340: universities. There were 259 studen
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Within groups Total Test 4 Between
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Crooks, B. (2003). The combined use
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Appendix A 342
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teenager. Chapter four, “Identity
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