Towards Designing and Evaluating an Adaptable Assistance System for Technology-Enhanced Vocational Education

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Abstract

Intelligent tutoring systems collect learners’ traces in tech-nology-enhanced learning environments with the aim of guiding and improving their learning in real time. Research has succeeded in developing data models that optimize the prediction of learning outcomes. Accurate prediction, however, does not provide information on how to achieve the desired learning outcomes. Recent approaches emphasize an interdisciplinary design process using human-computer interaction and learning engineering methods. Accordingly, this paper introduces an adaptable assistance system for vocational education that is developed in an interdisciplinary collaboration between learning and computer science experts. The assistance system supports both the processes of self-regulated learning and collaborative knowledge building by enabling learners to individually choose from topic-specific and/or interaction-specific recommendations. The chatbot recommendations are derived from a learning suggestion middleware that evaluates xAPI statements. It is based on explanatory learner models that provide not only accurate predictions, but also interpretable and actionable insights into learners’ activities and their learning process. A graphical knowledge structure provides an overview of the learning content, learner’s progress and allows free navigation. Ideas on how to evaluate the assistance system in scenarios of self-regulated learning and workplace learning will be outlined.

Details

Original languageEnglish
Title of host publicationResponsive and Sustainable Educational Futures - 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings
EditorsOlga Viberg, Ioana Jivet, Pedro J. Muñoz-Merino, Maria Perifanou, Tina Papathoma
PublisherSpringer, Cham
Pages618 - 623
Number of pages6
ISBN (electronic)978-3-031-42682-7
Publication statusPublished - 28 Aug 2023
Peer-reviewedYes

Publication series

SeriesLecture Notes in Computer Science, Volume 14200
ISSN0302-9743

Conference

Title18th European Conference on Technology Enhanced Learning
Abbreviated titleEC-TEL 2023
Duration4 - 8 September 2023
Website
LocationUniversidade de Aveiro
CityAveiro
CountryPortugal

External IDs

doi 10.1007/978-3-031-42682-7_51
ORCID /0000-0002-1972-1567/work/142246296
Scopus 85172033551
Mendeley 3f697ea4-0109-3672-9173-ebf3768f9d3a

Keywords

Keywords

  • Technology Enhanced Learning (TEL), Vocational education and training, Intelligent tutoring system, recommendations, Chatbot, Technology Enhanced Learning (TEL), Intelligent tutoring system, Vocational Education and Training, Recommendations, Chatbot, Intelligent Tutoring System, Technology-Enhanced Learning Environments

Library keywords