Breaking barriers: empowering non-STEM students in data skills through inquiry-based and collaborative learning

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Non-STEM students frequently undervalue vital data skills such as reading, analysing, arguing with data, and numerical proficiency. Many in non-STEM courses perceive barriers, mistakenly thinking these skills are exclusive to STEM disciplines. To overcome this misconception, tailored teaching approaches are crucial for breaking down barriers, integrating non-STEM students into the learning process, and enhancing their data skills.

This study implemented an inquiry-based and collaborative-based learning in the Data Analysis, Tools, and Applications module in the academic year 2021-2022 which consisted of 140 students (23 computing, 117 business). The 50-minute online session used Mentimeter for engagement through questioning, quizzes, and polls, integrating real-world case scenarios. A 2-hour on-campus practical session implemented collaborative learning, wherein student groups collaboratively tackled problems or tasks related to the weekly topic. This involved brainstorming and collective problem-solving efforts. Evaluation comprised a self-directed questionnaire adapted from the National Research Council of the United States National Academies of Sciences, covering various aspects. The post-teaching formative test assessed different learning levels using multiple styles (MCQ, Drop-in answer, Fill-in-the-blank) based on Bloom’s Taxonomy—recalling information, summarising ideas, and applying knowledge to new problems.

Of the 117 business students, 35% (41 students) responded to the questionnaire. Notably, 59% found lectures satisfactory, 47% commended the inquiry-based approach, and 48% praised visual aids. Instruction and online materials were considered fine by 55%, and 62% rated assessments as fine. Overall, students expressed strong positive opinions. Regarding the learning experience, 55% found the pace suitable, and 55% felt the content difficulty was manageable. 52% of Students expressed they learned in a fair amount. In the formative assessment with 76 participants (63 business, 13 computing), the average score was 20.64 out of 35 (SD = 5.32). An independent-samples t-test comparing average formative test scores in STEM and non-STEM students showed no significant difference, t(74) = -1.66, p = .10, despite slightly higher scores for STEM students (M=22.85, SD=6.22) compared to non-STEM students (M=20.19, SD=5.06). The results suggest no significant difference in data skills between the two groups. Importantly, the findings indicate a reduced skill gap by the end of the sessions, demonstrating that non-STEM students can achieve knowledge and data skills similar to STEM students.

The study reveals that inquiry and collaborative learning positively impact students in non-STEM courses, enabling them to acquire data skills traditionally associated with those in STEM domains. Effective teaching of foundational data skills to non-STEM students is achievable with appropriate methods. The 'learning by doing' approach proves instrumental in breaking down disciplinary barriers, fostering a seamless transfer of knowledge and skills. These findings emphasise the need for further exploration and implementation of inquiry and collaborative-based methodologies in education across diverse settings, aiming to broaden the scope of student learning.
Original languageEnglish
Title of host publicationINTED2024 Proceedings 18th International Technology, Education and Development Conference March 4th-6th, 2024 Valencia, Spain
EditorsLuis Gómez Chova, Chelo González Martínez, Joanna Lees
PublisherIATED Academy
Number of pages7
ISBN (Electronic)978-84-09-59215-9
Publication statusPublished - 4 Mar 2024
Event18th International Technology, Education and Development Conference - Valencia, Spain
Duration: 4 Mar 20246 Mar 2024


Conference18th International Technology, Education and Development Conference
Abbreviated titleINTED2024

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