The Go-Lab Platform, an Inquiry-learning Space: Investigation into Students' Technology Acceptance, Knowledge Integration, and Learning Outcomes

Utilizing an inquiry-learning space (ILS) via the Go-Lab platform, we investigated students' technology acceptance, knowledge integration [KI] process, and learning outcomes of both the high-achiever KI student and low-achiever KI student. This study aimed to understand how students engage in knowledge integration tasks using an inquiry-learning space to learn Mendelian genetics and realize the relationship between student KI and domain knowledge. Using a quasi-experimental design, we examined 41 seventh-grade students in Taiwan completing Mendelian genetics KI tasks in ILS, pre/post-testing of domain knowledge tests, and a technology acceptance questionnaire. The analysis of students' interaction in the ILS and domain knowledge tests was conducted through descriptive statistics, t-tests, Pearson's correlation, and content analysis to indicate the direction and relationship between students' KI processes and learning outcomes. A technology acceptance questionnaire was analyzed through descriptive statistics and Pearson's correlation to reveal whether students accepted learning on the Go-Lab platform. The study showed that (i) students responded positively to the perceived usefulness of the Go-Lab platform, (ii) the high-achiever KI students could gradually construct links from simple to complex and diverse among genetic ideas, and the low-achiever almost built simple links, but (iii) the high-achiever and low-achiever KI students had similar learning outcomes. These findings have implications that the instruction design of knowledge integration tasks promotes students' Mendelian genetics conceptual understanding and KI progress.

Automated summary

Through the Go-Lab platform's inquiry-learning space (ILS), we investigated students' technology acceptance, knowledge integration (KI) process, and learning outcomes. The study revealed that students responded positively to the usefulness of the platform, high-achiever KI students constructed complex and diverse links among genetic ideas while low-achiever KI students only built simple links. However, the learning outcomes were similar for both high-achiever and low-achiever KI students.