Intelligent model-based feedback: helping students to monitor their individual learning progress

Automated knowledge assessment methodologies provide the technological background for producing instant feedback at all times during the learning process. It is expected that the availability of such individual, dynamic, and timely feedback supports the learner's self-regulated learning. This chapter provides the theoretical background for an intelligent feedback approach and introduces two automated model-based feedback tools: TASA (Text-Guided Automated Self Assessment) and iGRAF (Instant Graphical Feedback). The chapter concludes with a discussion of the two feedback approaches and future research directions. © 2012, IGI Global

Learning Factories 4.0 in technical vocational schools: can they foster competence development?

Learning Factories 4.0 are thought to prepare vocational students for the challenges of Industry 4.0. The implementation of those interconnected Learning Factories 4.0 at technical vocational schools may promote the development of subject-related technical competencies as well as multidisciplinary digital competencies. Still, research is scarce with regard to the development of competencies supported through Learning Factories 4.0 in technical vocational schools. Hence this research focusses on subject-related technical and multidisciplinary digital competencies of technical vocational students change due to different levels of Learning Factory 4.0 interaction over time. Three subsequent competence tests with N = 63 technical vocational students were conducted. Findings indicate the benefits of integrating Learning Factories 4.0 for developing subject-related competencies in technical vocational schools. However, the study could not identify a positive development of multidisciplinary digital competencies. The findings of this study can help educators to further develop learning environments with support from Learning Factories 4.0 as well as preparing their learners for the demanding competencies of Industry 4.0

Digital learning resources and ubiquitous technologies in education

This research explores the educators' attitudes and perceptions about their utilisation of digital learning technologies. The methodology integrates measures from ‘the pace of technological innovativeness’ and the ‘technology acceptance model’ to understand the rationale for further ICT investment in compulsory education. A quantitative study was carried out amongst two hundred forty-one educators in Malta. It has investigated the costs and benefits of using digital learning resources in schools from the educator’s perspective. Principal component analysis has indicated that the educators were committed to using digital technologies. In addition, a step-wise regression analysis has shown that the younger teachers were increasingly engaging in digital learning resources. Following this study’s empirical findings educational stakeholders are better informed about how innovative technologies can support our students. In conclusion, this paper puts forward key implications and recommendations for regulatory authorities and policy makers for better curricula and educational outcomes.peer-reviewe

Multidisciplinary digital competencies of pre-service vocational teachers

Developments of Industry 4.0 require a set of multidisciplinary digital competencies for future vocational teachers, consisting of specific knowledge, motivational aspects, cognitive abilities and skills to fulfill the demands of digitally interconnected work situations. The competence model that is adapted from future work scenarios of vocational apprentices in Industry 4.0 includes attitudes towards digitization and handling of digital devices, information literacy, application of digital security standards, virtual collaboration, digital problem solving as well as a demonstration of reflective judgment of one’s actions in an interconnected and digital environment. Structural equation modeling was used to assess N = 205 pre-service vocational teachers between 18 and 35 years of age. The findings indicate the relationship of the proposed dimensions, measured through external- and self-assessments validate the proposed structure of the multidisciplinary digital competencies. However, attitude towards digitization can predict the self-efficacy of the relevant Multidisciplinary Digital Competencies but not the actual achievement in an external assessed scenario. Nevertheless, this study confirms that self-assessed multidisciplinary digital competencies can predict achievement in an external and qualitative-assessed competence test. Fit indices show an acceptable model conception, the reliability and construct validity of the model were confirmed. Findings suggest that the attitude towards digitization and the application of digital security standards are important, whereas the ability to solve digital problems seems to have a weak relation to the general multidisciplinary digital competencies of pre-service vocational teachers

Diagnose lernabhängiger Veränderung mentaler Modelle : Entwicklung der SMD-Technologie als methodologisches Verfahren zur relationalen, strukturellen und semantischen Analyse individueller Modellkonstruktionen

Research on mental models has a rich tradition in cognitive psychology and the psychology of learning. Johnson-Laird (1983) and Gentner & Stevens (1983) were the first authors to attrib-ute special significance to mental models in their publications. Seel (1991) then expanded on these ideas in the German-speaking world with an extensive treatise on Knowledge of the world and mental models. The significance of this research approach has since been confirmed in numerous subsequent publications (Dinter, 1993; Dutke, 1994; Seel, 1999a; Al-Diban, 2002; Held et al., 2006). In the present study, I would like to contribute to this discussion from a methodological per-spective. The central assumption of the study is that an objective, reliable, and valid diagnosis of learning-dependent change in mental models requires not only theoretical examination of the construct of mental models but also the development of an instrument for their diagnosis (see Ifenthaler & Seel, 2005). The newly developed SMD technology enables the automated and com-puter-aided diagnosis of externalized models independent of content domain. The externalized models are diagnosed on three levels, each with a different focus. The central research question as to whether, and if so how, mental models change in the course of the learning process is investigated in three experimental studies (N = 106). The longi-tudinal design of the studies enables a precise diagnosis across a total of seven points of meas-urement. In addition, experimental variations and differences between study groups allow an analysis of pedagogical interventions during the learning process. The results demonstrate that the SMD technology enables a precise diagnosis of learning-dependent changes in mental models on all three levels: surface structure, matching structure, and deep structure. It was possible in the three experimental studies to detect a learning-dependent change in mental models on the relational and the structural level. Additionally, the semantic structure of the externalized models proved to be more closely similar to the explanation model than to the expert model. The study concludes with a discussion of the empirical findings and a research outlook which clearly demarcates their range of application. Last but not least, it is shown that the empiri-cal findings open up further fields of research and potential for promising developments in men-tal model research

Ethische Perspektiven auf Künstliche Intelligenz im Kontext der Hochschule

Im Kontext der Hochschule werden vermehrt Daten und Algorithmen zur Unterstützung von Lernen und Lehren, für Assessments, zur Weiterentwicklung von Curricula sowie zur Optimierung von Hochschulserviceangeboten eingesetzt. Frühzeitig wurde das Spannungsfeld von Künstlicher Intelligenz (KI) in der Hochschule zwischen Potentialen und ethischen Grundsätzen erkannt. Vorliegende konzeptionelle und empirische Beiträge zu Ethik und KI im Kontext der Hochschule zeigen, dass Datenschutz und Persönlichkeitsrechte einen zentralen Problembereich bei der Implementation von KI darstellen. Aus holistischer Sicht eröffnet der vorliegende Beitrag ethische Perspektiven auf KI im Hochschulbereich. Hochschulen müssen sich der Datenschutzthemen und ethischen Leitprinzipien, die in Verbindung mit KI stehen, annehmen. Ein Kernproblem beim Einsatz von KI in Hochschulen ist die Kontextabhängigkeit, Fragmentierung und Verzerrung verfügbarer Daten. Ziel der aktuellen Forschung sind Systeme mit KI, die theoretisch fundierte und transparente Datenanalysen mit pädagogisch relevanten Indikatoren und verlässlichen Interventionen ermöglichen. Es wird ein Diskurs um ethische Leitprinzipien im Zusammenhang mit KI im Kontext der Hochschule angeregt. Daraus sollen auf KI basierte Fehlentscheidungen vermieden und Schäden für Beteiligte der Hochschulen abgewendet werden. (DIPF/Orig.)In the context of higher education, data and algorithms are increasingly being used to support learning and teaching, for assessments, for the further development of curricula and to optimize university service offers. The tension between the potential of artificial intelligence (AI) and ethical principles was recognized at an early stage. Existing conceptual and empirical contributions on ethics and AI in the context of higher education show that data protection and personal rights represent a key concern in the implementation of AI. From a holistic point of view, this contribution opens up ethical perspectives on AI in the context of higher education. Universities need to address the privacy issues and guiding ethical principles associated with AI. Key issues interrelated with the use of AI in higher education are the contextual idiosyncrasies and dependency as well as fragmentation and distortion of available data. The aim of current research are AI systems that enable theoretically sound and transparent data analyzes with pedagogically relevant indicators and reliable interventions. A discourse on ethical guiding principles in connection with AI in the context of higher education is encouraged. This should avoid wrong decisions based on AI and prevent damage to those involved in the higher education arena and beyond. (DIPF/Orig.

Insight into kognitive structure : Assessment, analysis, and instructional innovations

Strong theoretical foundations and precise methodology are always the one and only starting point for good research. Without sound foundations nothing follows, and thus a deep understanding of the theoretical assumptions of cognitive structure and methodology involved is mandatory for research on cognition and learning as well as for instructional design. Several research projects contribute to the overall scientific knowledge with regard to cognitive structure and its assessment, analysis, and instruction. Cognitive structure continued to be a key subject in different fields of research for more than a century. For good reason. Foundations from cognitive science, computer science, philosophy, and cognitive psychology describe the workings of the human mind in tasks of deduktive and inductive reasoning, especially for reasoning in uncertainty. They lead to theories of problem solving and to theories of learning and instruction which are both highly interdependent. The development of useful systems has always been a goal for scientists and engineers serving professional communities in the fields of instructional design and instructional systems development. This kumulative work outlines a research project which enables an insight into cognitive structure highlighting ways of assessment, analysis, and instructional innovations

Open Assessment Resources for Deeper Learning

Imagine a tutor or sessional instructor anywhere in the world who wishes to know something about what students know and can do. With knowledge about Open Assessment Resources (OAR), a repository is visited that is linked to many sites frequented by instructors and instructional designers. The website links existing OER activities with open assessment resource activity-prompts for online student responses. Within the assessment component of a selected OER, the instructor finds a searchable data bank of concepts linked to core content and activities related to what is being taught. The assessment activity-prompt packages can be made, modified or found an