Learning mathematics from worked-out examples: Analyzing and fostering self-explanations

Recent research has shown that learning from worked-out examples is of major importance for initial skill acquisition in well-structured domains such as mathematics. However, only those learners who actively process the presented examples profit noticeably from this learning mode. Specifically, the learning outcomes depend on how well the learners explain the solution steps presented in the examples to themselves (‘self-explanation effect”). In a series of studies on learning mathematics from examples, learners’ spontaneous self-explanations and instructional means used to encourage self-explanations were investigated. In this research, the following main findings were obtained. Most learners were rather passive with respect to their spontaneous self-explanations. Among the active and successful learners, two subgroups employing different self-explanation styles could be identified. With regard to the instructional means used to induce effective example processing, it turned out that to employ “learning by teaching” in order to stimulate explanation activities was of very limited use. Attempts to directly train for or elicit certain types of self-explanations were more successful. However, even in the latter case, self-explanations had inherent deficits (e.g., proneness to errors). Thus, we sought to design learning arrangements that try to integrate self-explanations with well-timed and well-adapted instructional explanations (e.g., from tutors) in order to enhance students’ problem-solving skills.     

Accounting for diverse missions: can classification systems contribute to meaningful assessments of institutional performance?

Tertiary Education and Management - Although they have been developed for a variety of purposes, classification systems for tertiary or postsecondary education institutions offer a foundation for...     

Ontology management and evolution for business intelligence

The amount of heterogeneous data that is available to organizations nowadays has made information management a seriously complicated task, yet crucial since this data can be a valuable asset for business intelligence. Ontologies can act as a semantically rich knowledge base in systems that specialize in information management. The present work investigates the potential of ontologies in supporting the information lifecycle within a corporate environment for business intelligence. The paper demonstrates the use of Heraclitus II, a framework that employs ontology management and evolution in the context of information management systems. The capabilities of the framework in facilitating information management and business intelligence are evaluated through a real-life case study from the life sciences industry.     

What types of functions may be the lower Bohl function of a diagonal discrete linear time-varying systems?

In this paper, we give the necessary and sufficient conditions for a function f to be a lower Bohl function of a diagonal discrete linear time-varying systems.     

Building Multicultural Competencies in School Counselor Trainees: An International Immersion Experience

The authors describe an international cultural immersion field experience, make recommendations for counselor educators who want to establish a similar program, and present an example of a student's reflection on the experience as recorded in the personal multicultural competency portfolio.     

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies can be taught (e.g., troubleshooting, mathematical proving). Is learning by such examples also effective, and do the same instructional design principles apply? We discuss the main findings of an own research program and of related studies that addressed such questions. We found that CLT’s basic design principles also hold true for heuristic domains: Reduce extraneous load by employing examples, maximize germane load by fostering self-explanations, prevent cognitive overload by pretraining in the case of difficult learning materials, and by focusing attention on the most relevant aspects. Other typical CLT assumptions (e.g., better provide information for novice learners) were not confirmed in its generality. The present findings extend the applicability of CLT but also identify some potentially too simplistic assumptions.     

Why Don't More Students Major in IS?

The large increases in the number of information systems (IS) majors about 10 years ago have been matched by equally large decreases in IS enrollments over the last few years. This article addresses the question of why students choose any major in general, and why students no longer choose to become an IS major in particular. We used a validated survey instrument and the responses from 163 students to examine this question in detail. Not surprisingly, we found that "genuine interest" in the subject was the most salient factor affecting the decision to major in IS. More surprising were what factors did not appear to influence this decision—for example, the promise of good job salaries, job security, the advice of others, or even the image of those who become IS professionals. Students seem aware that information technology employment opportunities exist; if job and salary issues contribute to choosing majors  other than IS , it is due to the perception of an unfavorable work/salary ratio for our field rather than one of job security or availability. That is, the amount of work to get an IS degree (the perception of harder-than-average courses) combined with (for many students) the perception of an undesirable amount of continuous training to keep an IS career just do not seem to balance with salary levels. These findings have important implications for the recruiting efforts of IS faculty seeking to attract more IS majors.     

FROM PISA TO EDUCATIONAL STANDARDS: THE IMPACT OF LARGE-SCALE ASSESSMENTS ON SCIENCE EDUCATION IN GERMANY

The German education system does not traditionally rely on standardized testing. However, when the Programme for International Student Assessment (PISA) study revealed an average performance of German students compared to other participating countries, a particular proportion of low-performing students, and remarkable disparities between the federal states, German policy makers decided for a major reform of the education system. A core piece of this reform was the introduction of National Education Standards. For science education, these standards were heavily influenced by the PISA results and its underlying framework. That is, with the standards, a paradigm shift took place from the German notion of Bildung towards the Anglo-American notion of literacy. With the introduction of these standards, a new field of empirical educational research was created: research on models of scientific literacy or competency models as a basis of benchmarking the standards. This article describes the German education system before PISA, summarizes the major findings from PISA, and describes how these findings informed the formulation of the performance standards for science education. It also details the measures undertaken to benchmark these standards. Finally, it provides insight into the issues with developing and benchmarking performance standards and points out future areas of research on evidence-based decision making in educational policy.