Technologies designed and developed in PELARS project - The way to enhance STEM education
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Standard
Technologies designed and developed in PELARS project - The way to enhance STEM education. / Friesel, Anna; Spikol, Daniel; Cojocaru, Dorian.
2017 27th EAEEIE Annual Conference (EAEEIE). IEEE, 2017.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Technologies designed and developed in PELARS project - The way to enhance STEM education
AU - Friesel, Anna
AU - Spikol, Daniel
AU - Cojocaru, Dorian
PY - 2017/6
Y1 - 2017/6
N2 - Practice-based Experiential Learning Analytics Research and Support (PELARS) is a project about learning and making. The PELARS project finds ways of generating analytics (data about the learning process and analysis of this data), which helps learners and teachers by providing feedback from hands-on, project-based and experiential learning situations. In this paper, we present our proposal for improving analytics education with hands-on, project-based and experimental scenarios for engineering students. This is done through teacher and learner engagement, user studies and evaluated trials, performed at UCV (University of Craiova, Romania) and DTU Diplom (Technical University of Denmark, Campus Ballerup, Denmark). The PELARS project provides technological tools and ICT-based methods for collecting activity data (moving image-based and embedded sensing) for learning analytics (data-mining and reasoning) of practice-based and experiential STEM.
AB - Practice-based Experiential Learning Analytics Research and Support (PELARS) is a project about learning and making. The PELARS project finds ways of generating analytics (data about the learning process and analysis of this data), which helps learners and teachers by providing feedback from hands-on, project-based and experiential learning situations. In this paper, we present our proposal for improving analytics education with hands-on, project-based and experimental scenarios for engineering students. This is done through teacher and learner engagement, user studies and evaluated trials, performed at UCV (University of Craiova, Romania) and DTU Diplom (Technical University of Denmark, Campus Ballerup, Denmark). The PELARS project provides technological tools and ICT-based methods for collecting activity data (moving image-based and embedded sensing) for learning analytics (data-mining and reasoning) of practice-based and experiential STEM.
KW - Design Methods
KW - Education
KW - Learning Analytics
KW - Prototyping
KW - STEM
KW - Visual programming
UR - http://www.scopus.com/inward/record.url?scp=85070369758&partnerID=8YFLogxK
U2 - 10.1109/EAEEIE.2017.8768603
DO - 10.1109/EAEEIE.2017.8768603
M3 - Article in proceedings
AN - SCOPUS:85070369758
BT - 2017 27th EAEEIE Annual Conference (EAEEIE)
PB - IEEE
T2 - 27th EAEEIE Annual Conference, EAEEIE 2017
Y2 - 7 June 2017 through 9 June 2017
ER -
ID: 360246609