July 2007 Volume 10 Number 3 - Educational Technology & Society

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learner should change category. The shell also maintains a student history. This is used to offer reports to the author either on an individual student’s progress, a student category’s progress, or to give a report on the course. Mixed-initiative REDEEM The version of REDEEM described above has been used in situations where a teacher is available who wishes to take responsibility for macro-adapting REDEEM (i.e., assigning material and strategies to learners via student categories). This has been the way REDEEM has been used in conventional classrooms (primary, secondary, and military). However, not all learning situations are teacher-led, and to allow REDEEM to be useful in informal and student-led learning, it seemed appropriate to create a version where learners macro-adapt REDEEM to suit themselves. Consequently in the mixed-initiative version of REDEEM, authors use the domain tools and strategy tools as described above, the student tools set up categories (but do not assign students to categories), and the macro-adaption tools prescribe a default strategy and a range of available strategies per category. Now when the students log in, they select one of the learner categories, and this now results in a default teaching strategy, which they can change to any of the other strategies that are available. For example, for a statistics revision unit available to university students, we created four categories (confident learner/reviser and unconfident learner/reviser). Each category was assigned a default strategy (e.g., confident reviser received “challenge me”) but could choose to one of six other strategies). This design is a trade-off between giving students significant choice yet only requiring minimal interaction (less than 30 seconds typically) to utilize this functionality. Empirical Studies To examine whether REDEEM could achieve its objective to be general across a range of domains and users and still be effective educationally, we needed to analyze both the authors’ and the learners’ experiences. Each type of user has different requirements and consequently the type of analysis needed to differ as well. Table 1 summarizes the main studies that have been conducted. Table 1. Description of REDEEM studies Study Purpose Subjects Course Location Author Primary Reference 1. Primary Usability, 3 teachers, 1 Introduction to University Teachers, Ainsworth, Shapes Functionality teacher shape and area Lecturer Grimshaw, & trainer Underwood, (1999) 2. Naval Usability, 2 trainers Comm. & Info University & Trainers Ainsworth, authors Functionality Systems naval sites Williams, & Protocols Wood, 2001). 3. Genetics at Uni. 4. Genetics in School 5. Navy full time Learning effectiveness Learning effectiveness Learning effectiveness 6. Undergrad Learning effectiveness 7. RAF Learning effectiveness 8. Undergrad Functionality, Mixed Learning Initiative effectiveness 86 students Genetics University Teacher Ainsworth & 14–16yrs Grimshaw (2004) 15 students, Genetics Secondary Teacher Ainsworth & 14–16 yrs School Grimshaw (2004) 19 students Comm. & Info HMS Trainer Ainsworth et al. 17–22 yrs Systems Protocols Collingwood (2003) 25 students, PC & University Researcher Ainsworth, 20–28 yrs Networking Williams & Wood (2003) 16 students, PC & RAF Researcher Ainsworth & 20–45 yrs Networking Waddington Fleming (2006) 167 students, Statistics University Lecturer Ainsworth & 18–20 yrs Fleming (2005) 25
Author-focused studies Studies 1 and 2 were the main author-focused studies and they were primarily concerned with usability and functionality. Primary (K–12) and secondary (high) school teachers, lecturers, and military instructors found it easy to use the tools to express, represent, and assess their teaching knowledge to create a learning environment within a feasible time scale. REDEEM’s usability has been assessed by asking authors to create learning environments either for their own class of learners or a set of hypothetical learners. Then teachers were interviewed throughout the process of creating the environments and about their satisfaction with the outcome. Initial training in the use of the REDEEM tools required between one and two hours. No author found the overall decomposition of the teaching process incompatible with his or her approach. REDEEM’s use of graphical and form-fill style interview tools has mostly proved simple and easy for authors to use. Time taken to author (once an existing suitable course has been found) has been acceptable, ranging from between 6 and 11 hours to author the four-hour course, Understanding Shapes (Study 1). In Study 4 a teacher took less than 25 hours to create two environments (around eight hours of instruction). Navy authors began by requiring <strong>10</strong> hours per chapter (around 6:1), which dropped to 6 hours by the end of authoring (around 3:1) (Study 2). It is not unrealistic to claim that creation of a REDEEM learning environments from an existing course can be done at a ratio of under five hours development per hour of instruction. In terms of functionality, overall, authors were pleased with the functionality that REDEEM offered. Compared to the original courseware or to courses authored by others, they all felt their learning environments were more suitable for their classes’ needs. Classroom teachers and military instructors used REDEEM in very different ways, with teachers focusing more on personalization. The teachers wanted to structure the domain material in ways that reflected their own beliefs and to create multiple student categories with unique strategies. In contrast, the military authors used REDEEM to create a single teaching strategy that reflected their own preferred strategy rather than the courseware designer’s strategy. What both groups had in common was the value they placed on increasing interactivity by adding questions and reflection points. However, these studies have revealed some interesting dilemmas about REDEEM’s design. Firstly, REDEEM requires users to shift from storyboarding to knowledge-based authoring. The most problematic part of this is domain sequencing, with authors describing characteristics of a page (e.g., familiarity and complexity) and the shell computing a route. However, this proved too time-consuming, was difficult for authors to visualize, and so was unpopular and resisted. Unfortunately, knowledge-based authoring ignores the important role that narrative plays for authors and learners when they are interacting with new material. In retrospect, we would stick to knowledge-based authoring for interactivity but use a more narrative-based approach to structure the domain content. The second concern is with the adaptive features of REDEEM, which allow the shell to compute its own route through material and to change student category (if desired), and so allow students to receive different teaching strategies. This proved very unpopular with all authors as they were reluctant to surrender control to the system. This limits the functionality that REDEEM can offer, turning it into a courseware authoring tool rather than its original intended goal of intelligent tutoring system authoring tool. The final concern is time efficiency. Authors need to create learning environments in a time-efficient way. REDEEM achieves a ratio of around three to five hours of authoring to one hour of instruction when a trained author, familiar with the domain and with teaching, creates an environment from imported domain material. But it does not include time to locate the domain material that meets their needs. However, many authors felt that the 5:1 ratio was not fast enough. If authors had been happy to leave decisions to REDEEM, some of this time could have been reduced (e.g., authors often hand-coded a sequence of material when the shell would have produced the same route automatically). Authors also often spent a considerable amount of time on details that potentially may not have been too important (e.g., one teacher edited every help message to include a full stop after each message). However, on the positive side, one of the features that teachers appreciated most was the way that REDEEM allows quick assignment of different strategies and content to different student categories. Analysis of authoring times suggests that this is normally achieved in less than 30 minutes, irrespective of the size of the course. 26
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Page 3 and 4: Advertisements Educational Technolo
Page 5 and 6: Distinguishing between games and si
Page 7 and 8: “sometimes” is less demanding t
Page 9 and 10: Figure 2. From generic skill to lea
Page 11 and 12: The large window on the left presen
Page 13 and 14: define competencies of individual a
Page 15 and 16: competency is composed of a single
Page 17 and 18: Generic Skills Classes 1 2 3 Receiv
Page 19 and 20: Figure 6. Extension of the competen
Page 21 and 22: Competency scale By combining the g
Page 23 and 24: activities, and resources present i
Page 25 and 26: Conclusion The importance given to
Page 27 and 28: Ainsworth, S. (2007). Using a Singl
Page 29: different instruction. For example,
Page 33 and 34: egression showed that students were
Page 35 and 36: REDEEM is now a senior citizen in t
Page 37 and 38: Chieu, V. M. (2007). An Operational
Page 39 and 40: When students discuss with peers, t
Page 41 and 42: COFALE as a learning environment an
Page 43 and 44: COFALE supports a set of predefined
Page 45 and 46: Tom is asked to prepare a list of g
Page 47 and 48: 45-minute-long lecture and 2-hour-l
Page 49 and 50: as an easy-to-use technological mea
Page 51 and 52: Spiro, R. J., & Jehng, J. C. (1990)
Page 53 and 54: learning settings. However, such a
Page 55 and 56: introduced in the LOCO-Cite ontolog
Page 57 and 58: ‘virtual subsection’) of the LO
Page 59 and 60: Accordingly, TANGRAM provides stude
Page 61 and 62: learning environment is to define t
Page 63 and 64: Acknowledgment This work is support
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Page 67 and 68: wikis and blogs (or at least, colle
Page 69 and 70: The darker side of social software
Page 71 and 72: for the beetles, whose guts act as
Page 73 and 74: The principle of sociability The pr
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Page 79 and 80: We perceive adaptivity and personal
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Mixed-method evaluation approach tr
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Garden of Knowledge - with a commun
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equirements for collaborative adapt
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Law, E. L.-C., & Hvannberg, E. T. (
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Wang, T. I., Tsai, K. H., Lee, M. C
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2.3 Recommendation Model Survey In
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Figure 1. The portion of the concep
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STEP4: Associated with concepts in
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A modified TF-IDF approach is used
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P(CK j x LOM ) = k NW max ∀ T∈
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4.2.2 Correlation-based algorithm I
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content feedback, it can be intuiti
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66% improvement in average, and, wh
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(a) (b) (c) Figure 10. Comparisons
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index.aspx. ADL-2 (2001). Advanced
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Wolpers, M., Najjar, J., Verbert, K
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activity is taking place. For examp
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Figure 2: The CAM schema elements (
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• Context: the context element ca
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4.1 Generation of Attention Metadat
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addition, such keywords can be extr
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Action related data, data about sea
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Braun, S., & Schmidt, A. (2006). Do
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El-Bishouty, M. M., Ogata, H., & Ya
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collaboration (Ogata, et al., 1999)
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In case of LOI value is equal or cl
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Also, the learner can click on an e
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System Evaluation An experiment was
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In the fifth phase, 89% of the stud
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Fischer, G., & Konomi, S. (2005). I
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application for specific needs, whi
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(4) Multimedia: The truth is that e
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Program Company Price OS 6 eZediaMX
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Program Text editor Text import for
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Program Sound Formats Image Formats
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Program Image Painting Export Scrip
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Program Effects Needs player 5 Easy
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Program WYSIWYG Design Interactivit
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the grades awarded to the programs
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Grade Image formats Sound formats V
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Figure 3. Adequacy of image formats
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Animating objects, pictures, etc.,
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Educational overview Having taken m
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In summary, the final outcome is th
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Developing the Interactivity Survey
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technique. be treated as a desired
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55. A lecture in which student lear
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specific conclusions that researche
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Discussion and conclusion Although
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Juwah, C. (2003). Using peer assess
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Publish results Set a few goals for
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familiarity with computer terms, ex
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provide a framework for the integra
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tool themselves, and then gauge its
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associated with the effective use o
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portrayed as even more time-consumi
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Clarke, B. (2001). Corporate curric
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Neal, E. (1998). Using technology i
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Yearwood, J., & Stranieri, A. (2007
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entertaining (Neuhauser 1993). The
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in being addressed with the sequent
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The GAAM represents reasoning to a
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Other situations have more serious
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Figure 6. NARRATE phase screen afte
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The narration at Step 10 informs th
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very large degree of free-will has
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Rumelhart, D. E. (1975). Notes on a
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The School of Business at Universit
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Authentic assessment and OBOW exams
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iii. The assessment asks the studen
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world problems in relation to the s
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Herrington, J., & Herrington, A. (1
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services required by most clients i
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Wisdom. J. P., White, N., Goldsmith
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Work outside the U.S. has also prom
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of the Telecommunication Act, and t
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Parent-advocate respondents also re
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school administrators may be persua
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of legal requirements for accessibl
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Thus, while we have reason to belie
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underlying structure of the two pri
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still not familiar with its use; in
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Table 3: An Analysis of Different V
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of males. Secondly, as far as age w
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Conclusion This study examined the
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Sandholtz, J. H., Ringstaff, C., &
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The design and validation of a text
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Predetermined goal of a game The pr
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A true, precise and valid model “
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Bain, C., & Newton, C. (2003). Art
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Prensky, M. (2005). Adopt and Adapt
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opportunities based on studying dif
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The game -called Chase the Cheese-
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another token. Other tokens further
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The system is organized in differen
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“to produce a single product or p
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(e.g., cheese) or loses the game (a
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collaboration is not an easy task.
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Collazos, C., Ortega, M., Bravo, C.
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Soller, A., & Lesgold, A. (2000). K
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Is the usual hierarchical organizat
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The final step 7 in the procedure i
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This methodology is summarised in F
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‘IsBasisOf’, ‘HasConstraint
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The presented results are a reflect
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‘HasExample’, and ‘HasFurther
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DCMI (2003). DCMI Metadata Terms, R
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Literature review Astronomy educati
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Systems of type I provide different
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night. To prevent students from get
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Figures 2-5 display screenshots of
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Results of the study reveal the imp
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vertical axis leads to the disappea
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Dede, C., Salzman, M., Loftin, R. B
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Trumper, R. (2000). University stud
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ased on pre-defined adaptation rule
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Therefore, the higher-level items o
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common prefix with the existing pa
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later should be omitted (presented
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5.1 The Average Length of each Sequ
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Recall 6. Discussion 0.8 0.7 0.6 0.
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easily take lessons in a good learn
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Laborda, J. G., & Royo, T. M. (2007
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Chapter 8, Online reference tools,
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Kenyon, D. M., & Malabonga, V. (200
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and concise manner (e.g. Weeding =
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stream are chapters 7 and 8 which f
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