PRInK: Environmental virtual interactive based education and learning model for STEM motivation

Abstract

Pollution from quarry activities has a substantial environmental impact on many countries. This issue should be addressed accordingly as its impact may introduce various health-related problems to the surrounding community. One alternative is to increase awareness for the younger generation and society at large. However, environmental data modelling, specifically on quarry activities, has thus far targeted engineers and professionals, not school children, such as for knowledge exploration or learning material. At the same time, the number of students enrolling in STEM courses is continuously declining. Hence, this research aims to develop the environmental virtual interactive based education and learning model called PRInK to foster STEM education. Five components of the proposed model were identified: a) Computer-Assisted Learning; b) Motivation Level; c) Green Environmental Data; d) Learning Outcome; and e) Problem Context. The actual environmental scientific data were used in the simulation and visualisation. Experts in these fields verified the components. The result of the analysis reveals 17 groups of elements, which were further categorised into 58 sub-elements. The model then was validated through prototype development and users validation. The testing and validation of the prototype were carried out on secondary school children, with the results proving the usability and practicality of the model and showed the increased STEM motivation and interest. The PRInK model and the prototype increase society’s awareness about environmental issues starting from school, increase STEM interest and improve the overall quality of life through a shared understanding for future generations.

Current trends and developments in the application of digital tools and implementation of environmental awareness and sustainability in PBL-based STEM education: a dual systematic literature review

“…Since it is common practice to the couple (C)PBL and TEL (Technology-Enhanced Learning) (Nawi et al, 2019) or even its more advanced form of TEAL (Technology-Enabled Active Learning) (Shay et al, 2020), the most common component of these models was the technology as mentioned above assisted learning in many forms, especially Computer-Assisted Learning (Yahaya et al, 2021;Molan et al, 2022).…”

“…A minority (n=3) of the collected articles were based mainly on the development of a specific framework (Nawi et al, 2019) or model for (not necessarily only) environmental education, which put the focus of the entire learning process on the students, e.g., IGNITE (Dotson et al, 2020) or PRInK (Yahaya et al, 2021). However, since Nawi et al tested their framework on a specific topic, we also classified their article as a case study.…”

“…The latter was done implicitly in some articles (e.g., Rico et al, 2021) and more explicitly in others. For example, Molan et al ( 2021) classify even more precise outcomes (learning objectives) for each step of the virtual PBL-based learning tool they designed -the most poignant examples of that are the three articles that involve different, precisely designed frameworks (Nawi et al, 2019) or models of learning (Dotson et al, 2020;Yahaya et al, 2021).…”

“…A final addition to the potential contributing factors is a capable assessment system which may be created by developments of specific components of the internal assessment system of the school to support the means and goals of the modernization (Yahaya et al, 2021) and by creating and operating an independent, external assessment system to provide a risk-based evaluation (Nawi et al, 2019), or both (Dotson et al, 2020).…”

“…Perhaps the most crucial contributing factor belongs to the teachers as individuals: their lesson planning practice has to enable said development processes; otherwise, the necessary learning tools cannot be adequately utilized. It is incredibly decisive when it comes to complex ICT tools (Molan et al, 2021;Shay et al, 2020), new or uncommon methods and practices (Molan et al, 2021;Rossano and Calvano, 2020) -especially new frameworks (Nawi et al, 2019) or learning models (Dotson et al, 2020;Yahaya et al, 2021).…”