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• WYSIWYG: The WYSIWYG stands for “What you see is what you get”. This design feature furnishes content creators with an intuitive view to develop their contents. Furthermore, the feature also saves lots of time from troublesome production checking, and the saved time can be further used to enrich learning contents. • Multimedia: This criterion indicates the supported multimedia types of the authoring tool. • Content/Test Item Production: This variable reveals the authoring tool’s ability of learning resource creation. In addition to the production resource types (content and test item), the resource execution environment is also taken into consideration (web/client based resource). • Adaptation: This factor indicates whether the production (content/test item) of the authoring tool is adaptable to accommodate to different learning devices, such desktop, PDA, cellular phone, and so on. • Course Organization: The course organization function furnishes teachers with organization and management functions to arrange learning resources in a systematic manner. Particularly, suchlike function can assist teachers with producing learning maps or sequencings to learners, and these productions can be further applied to LMS for achieving adaptive learning. • Standard: This variable shows the supported standards of the authoring tool, such as QTI, SCORM, and so on. • Client / Web: This criterion indicates the execution environment of the authoring tool. • Purpose: The design purpose of the authoring tool is determined by this criterion. To guarantee the quality of the evaluation, eight authoring tools have been selected into this comparison. Since the information technology advances rapidly, only the relevant research works published within the recent five years could be considered as our comparative candidates. As the MEAT is introduced in this article, the other authoring tools and their features are briefly introduced below. Note that not each candidate has a name, and it assigns alphabetical ID to the unnamed candidates for identification. • IWiLL (Kuo et al., 2004): This web-based authoring tool is integrated in the IWiLL learning system, and the aim is to create interactive multimedia contents for English learning. To shorten the content production process, movie clips and subtitles are transformed from DVD to online multimedia database, which allows teachers and content creators to insert multimedia into English learning contents and test items directly. With the supports from the tool, teachers can create content with their preferred design styles, and students can searching relevant contents by importing vocabularies. • A (Simon et al., 2005): The authoring tool supports single authoring for producing adaptable web-based contents. Creators who are interested in authoring by the tool should understand XHTML (Extensible Hyper Text Markup Language). To visualize the XHTML, three device simulators (PDA, smart phone, and WAP phone) have been integrated in the authoring environment for preview. • Test Editor (Romero et al., 2006): The Test Editor is designed for generating adaptable test items by single authoring approach. The generated test items are archived in a XML file, which are reusable and can be interpreted by test engines for assessment. In addition, both the adaptive and the classic linear tests are supported by the test engines. • FAÇADE (Zhan & Kurz, 2005): This tool supports single authoring for adaptable web-based content creation. The FAÇADE framework is a context-aware adaptable tool for single-source web pages. Users with the authoring tool can author with a WYSIWYG graphical user interface, and then the corresponding XHTML for devices will be automatically generated. • B (Wang et al., 2007): This study utilizes web 2.0 technology to design the rich-client authoring environment for creating learning contents which compatible with various e-learning standards without redundant efforts. When authoring with the tool, teachers can directly utilize available learning resources from backend server without pre-downloading into local host, and the index will be automatically made for connecting present authoring and external learning resources. • Mobile Author (Virvou & Alepis, 2005): Mobile Author allows instructors to design mobile Intelligent Tutoring Systems (ITS), which contains mobile contents and test items by both mobile phone and desktop. In addition, each student’s learning behaviors are stored in the long term student model of ITS for adaptive learning. • HyCo (García & García, 2005): The HyCo is an authoring tool introduced to facilitate the composition of hypertext, which are stored as semantic learning objects in backend database. The aim of the HyCo is authoring through a simple and extremely intuitive interface and interaction model. Following that, any teacher with a minimum computer background has the possibility of transforming his/her experience and knowledge into useful and quality hypermedia educational resources. 61
Table 1: Comparative analysis of authoring tools Criteria/Tools MEAT IWiLL A Test Editor WYSIWYG Supported Supported Not Supported Not supported Multimedia PowerPoint Web Page FLASH Audio files Video files Audio recording Content / Test Item Production Video recording Web-based content production / Web-based test item production Adaptation Flexible Authoring Content (Multiple Authoring) Test Item (Single Authoring) Course Learning Map Design Organization Tool Multimedia Database Image XHTML VoiceXML Web-based content production / Web-based test item production Web-based content production / No Text Image No / Client and Webbased test item production No Single Authoring Single Authoring No No No Standard SCORM No No No Client/Web Client Web Client Client Purpose Generation of Generation of English Generation of Generation of adaptable learning learning contents adaptable web-based adaptable test items contents and test items interfaces Criteria/Tools FAÇADE B Mobile Author HyCo WYSIWYG Supported Not supported Not supported Supported Multimedia Images Learning Object Text Multimedia database Repository Image Content / Test Web-based content Web-based content Web-based content Web-based content Item production / No production / No production / Web- production / No Production based test item production Adaptation Single Authoring No Single Authoring No Course Organization No No No Yes Standard No SCORM IEEE LOM TW LOM No LOM Client/Web Client Web Web Web Purpose Creation of adaptable Generation of general Generation of Generation of general web pages learning contents adaptive mobile contents and test items. learning contents Based on the selected criteria and authoring tools, Table 1 summarizes the comparative analysis result. Among the comparative candidates, only our tool can produce both adaptable learning contents and test items while supporting content exchange standard. In addition, the MEAT is the only tool which provides visualized user-friendly course organization function. From implementation perspective, the authoring tool can be implemented as client-based or web-based tool. With the client-based tool, it has richer and friendlier user interface, and the generation process can be done at local host 62
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April 2009 Volume 12 Number 2
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Abstracting and Indexing Educationa
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Engaging students in multimedia-med
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this study discusses computer-based
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Sampling for preliminary study One
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Part 2 Pearson correlation .349** 1
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Figure 1. Box and whisker plot of t
Page 15 and 16: characteristics and learning styles
Page 17 and 18: However, critical reflection and in
Page 19 and 20: novels, so they collected any relat
Page 21 and 22: 1. Theories of teaching: Comments m
Page 23 and 24: grammatical errors and basic writin
Page 25 and 26: Ho, B., & Richards, J. C. (1993). R
Page 27 and 28: Hwang, K.-A., & Yang, C.-H. (2009).
Page 29 and 30: e deduced from the Affective Domain
Page 31 and 32: Detection procedure Figure 1 shows
Page 33 and 34: avoided. Image processing is perfor
Page 35 and 36: falling asleep) as defined in this
Page 37 and 38: classmates or left their seats duri
Page 39 and 40: help teachers to recognize the lear
Page 41 and 42: Hsieh, P.-H., & Dwyer, F. (2009). T
Page 43 and 44: significant comprehension effects o
Page 45 and 46: Treatment 3 (keyword group): Studen
Page 47 and 48: Criteria of achievement measures Th
Page 49 and 50: esults. A correlational analysis de
Page 51 and 52: A 2 x 1 ANOVA analyzed the effect o
Page 53 and 54: References Aragon, S. R. (2004). In
Page 55 and 56: Raphael, T. (1982). Improving quest
Page 57 and 58: educing maintenance costs. The cont
Page 59 and 60: Synchronization functions According
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Page 65: Design of manipulation process The
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Page 73 and 74: Tan, O. S., Parsons, R. D., Hinson,
Page 75 and 76: At a deeper level, though, there wa
Page 77 and 78: theoretical assumptions. Two theore
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Page 81 and 82: slightly different. The group who c
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Page 85 and 86: edited and presented to the class u
Page 87 and 88: Figure 10. Screen captures from the
Page 89 and 90: Some of the concerns that emerge fr
Page 91 and 92: Ajayi, L. (2009). An Exploration of
Page 93 and 94: As a result of the confluence of di
Page 95 and 96: peers (Schellens et al. 2005). Sche
Page 97 and 98: The integration of discussion board
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Page 101 and 102: The pre-service teachers perceived
Page 103 and 104: Furthermore, the study demonstrated
Page 105 and 106: Schellens, T., van Keer, H., & Valc
Page 107 and 108: McKean, 2003). Instructors will see
Page 109 and 110: program at The Ohio State Universit
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frustrating the student). ITSs make
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• Link removal - advanced student
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Expert Module Expert Module’s mai
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Based on the questionnaire results
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students were told that their perfo
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thirds of the interviewed students
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Throughout the semester, students i
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human teacher or question developer
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To test the learning effectiveness
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APPENDIX A Computer Science and Sof
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Thus, the use of computers changes
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Specifically, two objectives were p
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Nonetheless, both teachers assign a
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48% 35% 53% similar similar 69% 42%
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Table 4: Students’ attitudes Stat
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activities. Specifically, the histo
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Huang, Y.-M., Huang, T.-C., Wang, K
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• Could recommended learning sequ
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Analysis of sequences prediction me
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Figure 4. The sorting of learning s
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The figures 5a and 5b illustrate th
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Learning sequence recommendation sy
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In this study, forty subjects were
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The potential for LSRS to promote l
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They pointed out that LSRS helped t
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Cover, T. M., & Thomas, J. A. (1991
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Related Efforts An Internet forum i
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with handheld devices and they were
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agent would direct learners to a le
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Mobile RSS Aggregator In order to s
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learning, such as posting question
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With novel technological support, m
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Shen, L., Wang, M., & Shen, R. (200
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as an ‘affective loop’, which r
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Figure 2 is an example of two-dimen
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preference was gathered through dat
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compute the heart rate (HR) as a fu
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sessions. Of all the 18 learning se
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Burleson, W., Picard, R. W., Perlin
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Wu, C.-C., & Lai, C.Y. (2009). Wire
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The wireless handheld learning envi
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the lengthiness of the scales, whic
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Nursing dictionary We constructed a
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them. The computers were networked
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“The major difference was that I
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questionnaire. We do not consider t
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Faruque, F., Hewlett, P. O., Wyatt,
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etween a user and the system. Addit
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Figure 2. A concept map representin
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C5.0 can help teachers to generate
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that a selected programming exercis
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differences between our system and
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1(students can complete without any
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The PADS sometimes assigned very di
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Corno, L. (2000). Looking at Homewo
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Hwang, W.-Y., Hsu, J.-L., Tretiakov
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listed these functions as allowing
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In the research presented in this a
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Research Tools Web-based learning e
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Table 1. Operational definitions of
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action, interaction, and outeractio
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for them was getting the answer as
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Table 6 shows the learners’ prefe
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Bell, P., & Winn, W. (2000). Distri
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Askar, P., & Altun, A. (2009). CogS
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elations, interactions and activiti
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Figure 3. A comparison of knowledge
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ontology will easily be extensible
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Figure 7. Visual Representation of
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Step 5: Use Boolean to combine the
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2) CogSkillNet provides classroom i
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Neo, M., & Neo, T.-K. (2009). Engag
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• Conversation and collaboration
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IMAGE 2 2. Problem identification I
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Methodology At the end of the proje
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presentation skills (m = 3.72), and
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6. Can’t be denying that, sometim
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Lambert, N. M., & McCombs, B. J. (1
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not detected in a previous study, t
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et al. (2001) studied the learning
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all the students. At the midpoint o
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The observed pairs were aware of be
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Table 2 shows the results from a mo
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Table 5: The distribution of time (
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As discussed in the section on prev
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McDowell, C., Werner, L., Bullock,
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Comprehension monitoring is the awa
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or roles in a context, such as “I
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Correlation coefficient was also co
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(a) Text 1 (b) Text 2 (c) Text 3 (d
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Table 3 shows that the average read
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Figure 10. Trace results of the les
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monitor their reading process and h
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Conn, S. R., Roberts, R. L., & Powe
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The technology-mediated groups, wit
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hybrid model of supervision was pos
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Our research indicates that the hyb
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Janoff, D. S., & Schoenholtz-Read,
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goal of using storyboards. But, thi
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In general, learning activities nee
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Furthermore, free subjects, such as
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Storyboarding Roots and related wor
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Referees, on the other hand, may wa
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Symbols Interpretation Defines a un
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Figure 4. Top-level storyboard for
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may take subjects such as practical
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network security information envir
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The concrete procedure and interact
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(e.g., for graduation) using such i
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Thus, academic education modeling b
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Feyer, T., Kao, O., Schewe, K.-D.,
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Richards, G. (2009). Book review: T
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expands the child’s proximal envi
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Chapter 6 exemplifies the activitie
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