STEM Learning and Career Orientation via IoT Hands-on Activities in Secondary Education

Abstract

This work studies the influence of IoT-driven educational activities and tools (software, hardware and educational material) in STEM education as well as their role as STEM related career enablers to young boys and girls. The study builds on previous related results and applies to over 60 young students that are involved in hands-on learning activities in the context of a summer school. The analysis is based on especially designed close-ended and open-ended questionnaires as well as in-class observations and focuses on age and gender aspects. The results confirm the overall positive stance of the students on the educational activities and show that the provided tools under consideration are well accepted and effectively used. Furthermore, students' choices regarding prospective future careers reveal that their views on STEM fields and related professions have significantly been enriched through their participation in the summer school.

Exploring the Learning Process and Effectiveness of STEM Education via Learning Behavior Analysis and the Interactive-Constructive- Active-Passive Framework

“…This further indicates that hands-on learning is suitable as a STEM education teaching strategy (Bradberry & De Maio, 2019; Chen et al, 2020; Thuneberg et al, 2018). Learners deepen the knowledge construction process by hands-on practice, thereby improving their learning effectiveness in STEM activities, in accordance with the literature (Chen et al, 2020; Glaroudis et al, 2019; Ziaeefard et al, 2017).…”

Internet-of-Things Curriculum, Pedagogy, and Assessment for STEM Education: A Review of Literature

“…Final/Capstone project reports, project demonstrations, video presentations, summative quizzes, design reports, pre-tests, and post-tests [34], [37], [38], [45], [46], [59], [78]- [80], [87], [117], [126], [127] Cumulative assessment of applying IoT skills and knowledge to solve real-world problems, student growth in IoT skills and knowledge before and after the course Indirect Quantitative Likert-style questionnaire, feedback surveys [32], [33], [37], [43], [44], [46], [48], [79], [117], [126]- [128].…”

“…Learning gains, student perceptions/attitudes, teamwork skills Indirect Qualitative Focus group interviews, online discussion forums, analysis of other student artifacts such as diary logs, one-on-one discussions with students [6], [34], [37], [43], [109], [117], [128] Insights into students attitudes/perceptions, factors creating resistance to active learning, and recommendations for future iterations…”

“…• Quantitative assessment methods reported in the literature include Likert Scale surveys to understand students' learning gains, perceptions of IoT activities incorporated in the instruction, expectations from the IoT course, and for collecting student feedback on engagement, impressions, and attitudes [32], [33], [37], [43], [44], [46], [48], [79], [117], [126]- [128]. Data collection using quantitative assessments is often conducted at the end of the course.…”

“…As with all survey-based data collection, an appropriate number of samples must be collected along with taking into account the statistical power and effect size [139], [140]. • Qualitative assessment methods reported in the literature include focus group interviews, analyzing feedback comments collected at the end of feedback surveys, analyzing comments on online support forums, and one-on-one interactions with students [6], [34], [37], [43], [109], [117], [128].…”