October 2007 Volume 10 Number 4 - Educational Technology ...

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and evaluation used in the Greek higher education system. Paper presented at the 2004 IEEE International Conference on Advanced Learning Technologies, August 30 – September 1, 2004, Joensuu, Finland. Law, C. K. (1996). Using fuzzy numbers in education grading system. Fuzzy Sets and Systems, 83 (3), 311-323. Liu, C. L. (2005). Using mutual information for adaptive item comparison and student assessment. Educational Technology & Society, 8 (4), 100-119. Ma, J., & Zhou, D. (2000). Fuzzy set approach to the assessment of student-centered learning. IEEE Transactions on Education, 43 (2), 237-241. McMartin, F., Mckenna, A., & Youssefi, K. (2000). Scenario assignments as assessment tools for undergraduate engineering education. IEEE Transactions on Education, 43 (2), 111-119. Nykanen, O. (2006). Inducing fuzzy models for student classification. Educational Technology & Society, 9 (2), 223- 234. Pears, A., Daniels, M., Berglund, A., & Erickson, C. (2001). Student evaluation in an international collaborative project course. Paper presented at the First International Workshop on Internet-Supported Education, January 08 - 12, 2001, San Diego, CA, USA. Wang, H. Y., & Chen, S. M. (2006a). New methods for evaluating the answerscripts of students using fuzzy sets. Paper presented at the 19 th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, June 27-30, 2006, Annecy, France. Wang, H. Y., & Chen, S. M. (2006b). New methods for evaluating students’ answerscripts using fuzzy numbers associated with degrees of confidence. Paper presented at the 2006 IEEE International Conference on Fuzzy Systems, July 16-21, 2006, Vancouver, BC, Canada. Wang, H. Y., & Chen, S. M. (2006c). New methods for evaluating students’ answerscripts using vague values. Paper presented at the 9 th Joint Conference on Information Sciences, October 8-11, 2006, Kaohsiung, Taiwan. Wang, H. Y., & Chen, S. M. (2006d). Evaluating students’ answerscripts based on the similarity measure between vague sets. Paper presented at the 11 th Conference on Artificial Intelligence and Applications, December 15-16, 2006, Kaohsiung, Taiwan. Weon, S., & Kim, J. (2001). Learning achievement evaluation strategy using fuzzy membership function. Paper presented at the 31 st ASEE/IEEE Frontier in Education Conference, October 10-13, 2001, Reno, NV, USA. Wu, M. H. (2003). A research on applying fuzzy set theory and item response theory to evaluate learning performance, Master Thesis, Department of Information Management, Chaoyang University of Technology, Taiwan. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353. 241
Gogoulou, A., Gouli, E., Grigoriadou, M., Samarakou, M., & Chinou, D. (2007). A Web-based Educational Setting Supporting Individualized Learning, Collaborative Learning and Assessment. Educational Technology & Society, 10 (4), 242-256. A Web-based Educational Setting Supporting Individualized Learning, Collaborative Learning and Assessment Agoritsa Gogoulou 1 , Evangelia Gouli 1 , Maria Grigoriadou 1 , Maria Samarakou 2 and Dionisia Chinou 1 1 Department of Informatics & Telecommunications, University of Athens, Greece // {rgog, lilag, gregor}@di.uoa.gr, dionisiagr@gmail.com 2 Department of Energy Technology, Technological Educational Institution of Athens, Greece // marsam@teiath.gr ABSTRACT In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve leaning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners’ knowledge level, (ii) participate actively in the assessment process in the context of self-, peer- or collaborativeassessment activities, (iii) work with educational environments, embedded or integrated in SCALE, that facilitate the elaboration of the activities and stimulate learners’ active involvement, (iv) use tools that support the synchronous and asynchronous collaboration/communication and promote learners’ interaction and reflection, and (v) have access to feedback components tailored to their own preferences. Also, learners have control on the navigation route through the provided activities and feedback components, personalizing in this way the learning process. The results revealed from the formative evaluation of the environment are positive and encouraging regarding the usefulness of the supported capabilities and tools. Keywords Learning, Collaboration, Assessment, Feedback, Adaptation Introduction An emerging trend in education worldwide is a movement of the focus from that of teaching to that of learning and from an individualistic and objectivist view of learning to a social constructivism view (Palinscar, 1998; Reigeluth, 1999; Vosniadou, 2001). The underlying principle behind the social constructivism view of learning is that knowledge is constructed by the active interaction of learner with the environment and the idea that the construction of knowledge is socially mediated. It is claimed that effective collaboration has proven itself a successful and powerful learning method (Soller, 2001). Collaborative learning activities immerse students in challenging tasks or questions and enable them to become immediate practitioners and develop higher order reasoning and problem solving skills. In this context, collaborative learning is becoming increasingly used and the advent of communication technologies has made computer-mediated collaboration possible. Along with the learning process, assessment is considered an important component of an educational setting. Assessment plays a significant role in helping learners learn when it is interweaved with learning and instruction instead of being postponed at the end of the instruction (Shepard, 2000). Moreover, assessment helps students to identify what they have already learned, to observe their personal learning progress and to decide how to further direct their learning process. As knowledge construction necessitates higher order thinking, new forms of assessment are required. Assessment methods such as self-, peer- and collaborative-assessment have been introduced in recent years aiming to enhance/promote learning and integrate assessment with instruction. Self-assessment refers to the involvement of learners in making judgments about their own work/performance and aims at fostering reflection on one’s own learning and work (Sluijsmans et al., 1999). Peer-assessment refers to those activities of learners in which they judge and evaluate the work and/or the performance of their peers, while in collaborative-assessment, learners and instructor collaborate in order to clarify objectives and standards/criteria, negotiate details of the assessment and discuss any misunderstandings that exist (Sluijsmans et al., 1999). Integral part of the assessment process and a key aspect of learning and instruction is considered feedback (Mory, 1996). Feedback should guide and tutor learners towards the achievement of the underlying learning goals as well as stimulate and cultivate processes like selfexplanation, self-regulation and self-evaluation (Chi et al., 1994). Cognitive researchers view each individual learner as paramount in mediating learning. The learner becomes the focus of the learner-instruction transaction and instructional sequence decisions and options are adapted to individual 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. 242
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October 2007 Volume 10 Number 4
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Abstracting and Indexing Educationa
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The Relationship of Kolb Learning S
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a question about learning together
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affordances of networked learning s
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included a unit on collaborative le
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on at different times and work indi
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• the numerous evaluation studies
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wanted to work. The same inquiry pr
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usability studies have a place in t
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Milrad, M., & Jackskon, M. (2007).
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information- and communication tech
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Interactive Examination, the studen
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Table 1. Criteria for grading OD st
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content. Differences in the attitud
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Even though further research on the
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Olofsson, A. D. (2007). Participati
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Etzioni (1993) points out that an i
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programme. They are rather construc
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to be that each individual trainee
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Bernmark-Ottosson, A. (2005). Demok
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The Knowledge Foundation (2005). IT
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Figure 1. Design Theories in contex
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attention as we frequently discuss
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Blog Reflection This design concept
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Narrative Structure (Form) Content
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Löwgren, J., & Stolterman, E. (200
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critique, neither do the single ind
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suggested by Ljungberg (1999b) we c
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the del.icio.us site (see figure 3)
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Device cultures It is not only the
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uilt using a camera-equipped PDA ru
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Jones, C., Dirckinck-Holmfeld, L.,
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Milrad, M., & Spikol, D. (2007). An
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components to be able to deal with
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compulsory throughout the project.
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only with their existing day-today
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As our work continues, we will try
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cognition as well as self-regulated
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Mobile mind map tool for stimulatin
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the pictorial knowledge representat
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Ericsson, K. A., & Simon, H. A. (19
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Al-A'ali, M. (2007). Implementation
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complex cognitive skills involve em
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Table 1. CAT and a linear mathemati
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It is agreed that the difficulty le
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Figure 7. Our newly added factors i
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question factors according to IRT;
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Instructure 1 Login User-ID Passwor
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Shute, V., & Towle, B. (2003). Adap
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distinguish between partial knowled
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esponse is identified, then the sco
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are stored in the answer record and
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2 (7) MNSQ = ∑WniZ ni ∑ Wni =
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in the course. A randomized block d
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To test whether ET can effectively
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course, more comparison tests could
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Fleischmann, K. R. (2007). Standard
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educational standards in practice t
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laboratory activities, which are bu
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process is currently a largely top-
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Hsu, Y.-S., Wu, H.-K., & Hwang, F.-
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evolution with computing technology
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Resources 0.55 0.72 e17 In my schoo
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teachers’ instructional evolution
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Regression models indicating relati
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of beliefs about integrating comput
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Sinko, M., & Lehtinen, E. (1999). T
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concept of social support. Lastly,
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Procedure Content analysis procedur
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and mice are out of order. I have t
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feature of supportive online groups
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Anderson, J., & Lee, A. (1995). Lit
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Schwab, R. L., Jackson, S. E., & Sc
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Investigating the problem An extens
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meets the anywhere, anytime require
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minimise housekeeping tasks and fre
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3. Join Group Discussion 4. Attend
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Figure 4. Learning Shell showing He
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engineering the Learning Shell so i
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Olfos, R., & Zulantay, H. (2007). R
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portion of CourseInfo requires that
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Table 2. Assignment evaluation resp
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E-3c. Likert scale on usability: Th
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organized in four groups, namely: T
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The correlations were not high enou
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Data illustrate some reliability an
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nature, some specific core objectiv
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Frederiksen, J.R., & Collins, A. (1
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Bottino, R. M., & Robotti, E. (2007
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The Text Editor allows the editing
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Mathematical content and structure
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Consolidation exercises Solution co
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As to course components, the activi
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handle more formal representations
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Lagrange, J. B., Artigue, M., Labor
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processed information was classifie
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Page 217 and 218: Initial Design Because the field-ba
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Page 229 and 230: Wang, H.-Y., & Chen, S. M. (2007).
Page 231 and 232: If the universe of discourse U is a
Page 233 and 234: we can see that S( X ) − S( Y ) S
Page 235 and 236: Example 1: Let Ã and B ~ be two va
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Page 249 and 250: enabling learner (subject) to work
Page 251 and 252: • Self-, Peer- and Collaborative-
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Page 255 and 256: Figure 3. A screen shot of the SCAL
Page 257 and 258: 2 nd study: Thirty-five students pa
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Page 261 and 262: Soller, A. (2001). Supporting Socia
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Page 265 and 266: Solution 2.2: Deliberately select h
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Page 275 and 276: Concept Mapping Concept mapping by
Page 277 and 278: Research Questions In order to dete
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Page 281 and 282: Tukey’s HSD post hoc test reveale
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student and teacher on the synchron
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Vogel, J. J., Vogel, D. S., Cannon-
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Cases The first set of ten case stu
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Kılıçkaya, F. (2007). Website re
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