Previous studies have demonstrated the learning benefit of personalized language and worked examples. However, previous investigators have primarily been interested in how these interventions support students as they problem solve with no other cognitive support. We hypothesized that personalized language added to a web-based intelligent tutor and worked examples provided as complements to the tutor would improve student (e- )learning. However, in a 2 x 2 factorial study, we found that personalization and worked examples had no significant effects on learning. On the other hand, there was a significant difference between the pretest and posttest across all conditions, suggesting that the online intelligent tutor present in all conditions did make a difference in learning. We conjecture why personalization and, especially, the worked examples did not have the hypothesized effect in this preliminary experiment, and discuss a new study we have begun to further investigate these effects.

Authoring tools for Intelligent Tutoring Systems are especially valuable if they not only provide a rich set of options for the efficient authoring of tutoring systems but also support controlled experiments in which the added educational value of new tutor features is evaluated. The Cognitive Tutor Authoring Tools (CTAT) provide both. Using CTAT, real-world "Example-Tracing Tutors" can be created without programming. CTAT also provides various kinds of support for controlled experiments, such as administration of different experimental treatments, logging, and data analysis. We present two case studies in which Example-Tracing Tutors created with CTAT were used in classroom experiments. The case studies illustrate a number of new features in CTAT: Use of Macromedia Flash MX 2004 for creating tutor interfaces, extensions to the Example-Tracing Engine that allow for more flexible tutors, a Mass Production facility for more efficient template-based authoring, and support for controlled experiments.

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In this work we are investigating the learning benefits of e-Learning principles (a) within the context of a web-based intelligent tutor and (b) in the “wild,” that is, in real classroom (or homework) usage, outside of a controlled laboratory. In the study described in this paper, we focus on the benefits of

The opinions and positions expressed in this practice guide are the authors ’ and do not necessarily represent the opinions and positions of the Institute of Education Sciences or the U.S. Department of Education. This practice guide should be reviewed and applied according to the specific needs of the educators and education agencies using it and with full realization that it represents only one approach that might be taken, based on the research that was available at the time of publication. This practice guide should be used as a tool to assist in decision-making rather than as a “cookbook.” Any references within the document to specific education products are illustrative and do not imply endorsement of these products to the exclusion of other products that are not referenced. U.S. Department of Education

project creates useful simulations for teaching and learning physics and makes them freely available from the PhET website

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Abstract: Technology-facilitated collaboration is extending the ways in which students and instructors interact within and beyond the classroom. Our paper describes how we effectively used Personal Response Systems (PRS), lecture slides, video archives, instant messaging, and course management software to extend interaction in a junior-level Computer Science course. Besides this

recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Keywords: computational modeling, cognitive modeling, instructional theory, machine learning, learning science, second language learning, mathematics learning, science learning, robust learning, learning theory, knowledge componentsExecutive Summary The volume of research on learning and instruction is enormous. Yet progress in improving educational outcomes has been slow at best. Many learning science results have not been translated into general practice and it appears that most that have been fielded have not yielded significant results in randomized control trials. Addressing the chasm between learning science and educational practice will require massive efforts from many constituencies, but one of these efforts is to develop a theoretical framework that permits a more systematic accumulation of the relevant research base. A key piece in such a theoretical framework is the development of levels of analyses that are fine enough to be supported by cognitive science and cognitive neuroscience, but also at levels appropriate to guide the design of effective educational practices. An ideal scientific solution would be a small set of universal instructional principles that can be applied to produce efficient

Designing E-learning is a combination of pedagogical design, usability and information architecture. E-learning environments should have intuitive interfaces and clear information design, allowing learners to focus on learning. However, there is often a mismatch between what an on-line educator thinks the learner would learn, and what a learner thinks he will, and then has learned from the course. In addition, there is sometimes a mismatch between how an educator wants to teach and what is represented on the interface by the instructional designers. Such mismatches affect the learner’s experience and his motivation for E-learning. In this paper, we will first discuss the source and nature of these mismatches. Next, we will discuss whether usability techniques in the HCI literature are appropriate for evaluating E-learning environments for the learner experience. We will then propose a combination of requirements elicitation and usability techniques for learner-centred design and evaluation of Web-based E-learning environments. The proposed methodology is based on our experience of conducting empirical studies for evaluating usersystem interactions in E-Commerce contexts.