English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Surveys show besides the number of students also the drop-out rates are increasing, especially in early phases of studying natural or engineering sciences. The research project “SensoMot Sensor Measures of Motivation for Adaptive Learning” tries to counter this development by means of improving the quality of teaching in the department of micro technology with the help of an adaptive e-learning system. For that purpose, the mediated learning content should be better adapted to the individual prior knowledge, competencies and motivational profiles of the learners. Furthermore, the continuous sensory data acquisition of physiological parameters of the learner shall be accomplished by current wearable technology. The paper presents first results in the form of conceptual determinations concerning self-reports and physiological measures, instructional design and adaptation techniques and further includes the early involvement of the subsequent users in the development process through an iterative, formative evaluation of prototypical solutions.

Adaptive E-Learning Technologies for Sustained Learning Motivation in Engineering Science - Acquisition of Motivation through Self-Reports and Wearable Technology