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Ronteltap, F. and Eurelings, A. (2002) Activity and interaction of students in an electronic learning environment for problem based learning, Distant Education, 23(1),11-22. Segers, M., Dochy, F. J. R. C., & Cascallar, E. (2003). Optimising new modes of assessment : in search of qualities and standards. Dordrecht ; Boston: Kluwer Academic Publishers. Sercu, L. (2006). The foreign language and intercultural competence teacher: the acquisition of a new professional identity. Intercultural Education, Vol 17, Issue 1, 55-72. [žita 2007-08-31]. Prieiga per Internet: Academic Search Premier (EBSCO) duomen baz. Somervell, H. (1993) Issues in assessment, enterprise and higher education: the case for self-, peer and collaborative assessment, Assessment and Evaluation in Higher Education, 18. Stiggins, R. J. (1994). Student-centered classroom assessment. New York: Merrill. Zubizarreta, J. (2004). The Learning Portfolio. Bolton, MA: Anker Publishing. Conference proceedings of Student Mobility and ICT: Can E-LEARNING overcome barriers of Life-Long learning?” 50
Explaining student learning preferences in a blended learning environment for learning statistics on the basis of student characteristics Dirk T. Tempelaar, Bart Rienties, Maastricht University, The Netherlands D.Tempelaar@ke.unimaas.nl, Bart.Rienties@erd.unimaas.nl Abstract: In the teaching of introductory statistics to first year students economics and business, the Maastricht University uses a blended learning environment that allows students to design a individualized environment by attuning available learning tools to personal preferences. The blended learning environment consists of tutorials based on the problem-based learning principle, lectures, independent learning and an electronic learning environment based upon knowledge space theory: ALEKS. Usage of only the first component is required; the usage of other components can be set according to individual preferences. In this study, we will focus on the intensity of the use of the electronic learning environment ALEKS and investigate the relationship between this and student background characteristics, such as learning style preferences and motivational variables. Data of about 2000 students taking this course is used. Introduction In this empirical study, we investigate in a large group of first year university students following an economics or business program, the revealed preferences for using the e-learning component in a blended learning environment for learning introductory statistics. This blended learning environment consists of tutorials based on the problem-based learning principle, lectures, independent learning and an electronic learning environment based upon knowledge space theory: ALEKS (Tempelaar et al., 2006). Except for the tutorial sessions, for which attendance is required, students can set the intensity for each of the components of the blended learning environment according their personal preferences. Some of these preferences become revealed, e.g. by measuring connect-time in the e-learning mode. This study aims to explain patterns in revealed preferences by individual differences in a range of determinants of learning processes: preferred learning approaches, metacognitive abilities, and achievement motivations. The Inventory of Learning Styles (ILS) instrument, developed by Vermunt (see Vermunt and Vermetten, 2004), has been used to assess preferred learning approaches. Students’ metacognitive abilities are operationalised by the recently developed self-report instrument Awareness of Independent Learning Inventory (Elshout-Mohr et al., 2005; Tempelaar, 2006), that presumes metacognition to be a three dimensional construct, comprising knowledge, skills, and attitudes. Expectancy-value models form the basis of an instrument measuring achievement motivations (Schau et al, 1995; Tempelaar et al, 2007). Schau’s version of the modern expectancy-value model distinguishes two expectancy factors dealing with students’ beliefs about their own ability and perceived task difficulty, a construct expressing subjective task-value, an affective task-related attitude, and the constructs interest and effort. Achievement motivations are measured ex ante and ex post, in order to be able to observe developments during the learning episode. Measurements for students’ preferences for e-learning are generated as log-data by the ALEKS electronic tutorial system. The adaptive tutorial system ALEKS The ALEKS system combines adaptive, diagnostic testing with an electronic learning & practice tutorial in several domains relevant for higher education. In addition, it provides lecturers an instructor module where students' progress can be monitored, educational standards can be adapted to a particular college, or course and other administrative tasks can be carried out. ALEKS is a commercial software product. The ALEKS assessment module starts with an entry assessment in order to evaluate precisely a student's knowledge state for the given domain (e.g. Business Statistics). Following this assessment, ALEKS delivers a graphic report analyzing the student's knowledge within all curricular areas for the Conference proceedings of Student Mobility and ICT: Can E-LEARNING overcome barriers of Life-Long learning?” 51
Page 1 and 2: Proceedings of Student Mobility and
Page 3 and 4: Contributions listed per session We
Page 5 and 6: Teaching Part-time Students Using C
Page 7 and 8: Description of Practices of Knowled
Page 9 and 10: Remediating Summer Classes and Diag
Page 11 and 12: • For a bridging course of this s
Page 13 and 14: computing and displaying geometrica
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Page 27 and 28: views. As the IOs staff has to coll
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Page 35 and 36: Additionally to the CIS each course
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References Dijsselbloem, J., e.a. (
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Findings So far, seventy-four stude
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Students’ Mobility, Acculturation
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Pedagogical Approaches Used For Pre
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• the teacher is a learner togeth
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learning. He pointed at the method
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Wieland, A., Brouwer, N., Kaper, W.
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The live learning lab was more than
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For the audience site, the camera s
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video/audio compression and competi
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applications for a typical presenta
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E-learning - Non-discovered Territo
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References Badania potrzeb w zakres
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Security Requirements and Goals for
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The implications of using this tech
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References Hinton, H., & Vanderwauv
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This is mainly due to the fact that
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students from one class session to
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Social Presence, Web-videoconferenc
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facilities. As Figure 2 shows, web-
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Instruments Expectations of the cou
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Table 1 Comparison of course useful
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As group collaboration and the cour
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Literature Scan on Online Remedial
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Most recent studies have focussed o
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The implementation of online educat
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Lefgren (2004); Kozeracki (2002); L
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Establishing a European Framework o
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Modelling Mobile Agent Mobility in
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f11 = Addressing f12 = Encoding f13
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Naming services The Sun Microsystem
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Lamport, L & Melliar-Smith, P. M.(1
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lecturers see all lectures they hav
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Figure 3. A content page of the Tec
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Digitizing Courses for Flexible Edu
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Figure 1. Amount of fragment views
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elaborate on the fragments in sever
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engaged in family and/or work life,
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and Services contributes to interna
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Furture prospects Physical student
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Towards a Dutch Remedial Education
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Hollins, E. R. (1996). Culture in s
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To realise this goal a consortium o
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Hybrid Learning as a Facilitator to
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are commonly associated with high c
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Table 3. Individual forum participa
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ecause of the huge investment in de
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Pere, R. (1982). Ako: concepts and
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facility with technology as an empl
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The subject of the advertisement is
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M Pete Nevin October 10 at 8:46pm H
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