Thursday 31 July, 16:00 - 17:30Chair: Gerhard Weber
Adaptation of Elaborated Feedback in e-Learning (page 235)Ekaterina Vasilyeva, Mykola Pechenizkiy, and Paul De Bra
Design of feedback is a critical issue of online assessment development within Web-based Learning Systems (WBLSs). In our work we demonstrate the possibilities of tailoring the feedback to the students' learning style (LS), certitude in response and its correctness. We observe in the experimental studies that these factors have a significant influence on the feedback preferences of students and the effectiveness of elaborated feedback (EF), i.e. students' performance improvement during the test. These observations helped us to develop a simple EF recommendation approach. Our experimental study shows that (1) many students are eager to follow the recommendations on necessity to read certain EF in the majority of cases; (2) the students more often find the recommended EF to be useful, and (3) the recommended EF helped to answer related questions better.
User-Centric Profiling on the Basis of Cognitive and Emotional Characteristics: An Empirical Study (page 214)Nikos Tsianos, Zacharias Lekkas, Panagiotis Germanakos, Costas Mourlas, and George Samaras
In order to clarify whether extending learners' profiles in an adaptive educational system to cognitive and emotional characteristics may have a positive effect on performance, we conducted an empirical study that consists of two subsequent experiments. The human factors that were taken into consideration in the personalization process were cognitive style, visual working memory span, control/speed of processing and anxiety. With the exception of control/speed of processing, matching the instructional style to users' characteristics was revealed to be statistically significant in optimizing their performance (n=219). On the basis of this empirical assessment, this paper argues that individual differences at this intrinsic level are important, and their main effect can be manipulated by taking advantage of adaptive technologies.
Re-assessing the Value of Adaptive Navigation Support in E-Learning (page 193)Sergey Sosnovsky, Peter Brusilovsky, Danielle H. Lee, Vladimir Zadorozhny, and Xin Zhou
In a recent study, we discovered a new effect of adaptive navigation support in the context of E-learning: the ability to motivate students to work more with non-mandatory educational content. The results presented in this paper extend the limits of our earlier findings. We describe the implementation of adaptive navigation support for the SQL domain, and report the results of the classroom evaluation of our approach. Among other issues, we investigate whether the use in parallel of two different types of navigation support could change the nature or the magnitude of the previously observed effect. Our study confirms the motivational value of navigation support in the new domain. We observe the increase of this effect after adding the concept-based navigation layer to the existing topic-based adaptive navigation service. The results of the navigational pattern analysis allow us to determine the major source of this increase.