Model-Based Inquiry in Computer-Supported Learning Environments: The Case of Go-Lab

Hovardas, Tasos; Pedaste, Margus; Zacharia, Zacharias C.; Jong, Ton de

doi:10.1007/978-3-319-76935-6_10

Cited by 8 publications

(3 citation statements)

References 61 publications

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“…Another study in remote-inquiry found that virtual simulations eased teachers to make instructional arrangements, and increased students' conceptual understanding of the subject matter of learning and maintained their learning motivation (Cook, 2022). Learning with virtual simulation is an integrated inquiry learning mode that can provide space to create a more interesting learning environment for students (Hovardas et al, 2018). The results of our current study are also reinforced by the findings of Brinson (2015) who synthesized empirical studies on virtual simulations, where almost all categories of learning outcomes (topic knowledge, content understanding, inquiry skills, analytical skills, scientific communication, social skills) can be trained by virtual simulation.…”

Section: Resultsmentioning

confidence: 99%

Nurturing Prospective STEM Teachers' Critical Thinking Skill through Virtual Simulation-Assisted Remote Inquiry in Fourier Transform Courses

Bilad

Anwar²,

Hayati³

2022

IJECE

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Alignment of inquiry learning has embarked on remote inquiry as a replacement for face-to-face inquiry. On the other hand, the current technological developments bring opportunities to use it as a learning resource to support critical thinking. The current study explores the impact of virtual simulation-assisted remote inquiry in Fourier transform courses on prospective STEM teachers' (PST) critical thinking (CT) skills. The experimental design employed a randomized pretest-posttest control group was employed. Two groups of samples were randomized: the experimental group, n = 30, and the control group, n = 30. The treatment of learning was different in each group. The experimental group was conducted by virtual simulation-assisted remote inquiry, while the control group was conducted by online learning without inquiry and simulation. The measured CT skills aspects included analytical, inference, evaluation, and decision-making measured by an essay test instrument. The results were then analyzed descriptively and statistically. The results confirm that the virtual simulation-assisted remote inquiry significantly improved PST CT in Fourier transform courses. The virtual simulation-assisted remote inquiry learning was better than courses with online learning without inquiry and simulation. The virtual simulation-assisted remote inquiry provided conceptual formation and application of concepts. It strengthened the opportunities for the PSTs to train their CT skills.

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Section: Resultsmentioning

confidence: 99%

Nurturing Prospective STEM Teachers' Critical Thinking Skill through Virtual Simulation-Assisted Remote Inquiry in Fourier Transform Courses

Bilad

Anwar²,

Hayati³

2022

IJECE

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“…The PhET project also provides a protocol extension known as PhET-iO [25,26]. Simulations that adhere to these guidelines are enhanced with a set of interoperability features that enable third parties to customise, integrate, and monitor [27] students while interplaying with PhET animations.…”

Section: Connection To Phetmentioning

confidence: 99%

Fostering scientific methods in simulations through symbolic regressions

Llorella,

Antonio Cebrián,

Corbi

et al. 2024

Phys. Educ.

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Two-dimensional computer and tablet PC physics simulations have proved to be effective in helping students understand the fundamental principles of physics and related natural processes. However, the current approach to using these simulations tends to follow a repetitive cognitive and procedural pathway, regardless of the specific physical concepts being explored or software environment being used. This approach involves manipulating the simulation interface and collecting data through interaction with controls, widgets, or other contextual elements. Students then attempt to determine how these experimental measurements align with established laws, interactions, or mechanisms, as the teacher might have previously explained. We believe that this approach, while appropriate for education, obscures scientific processes, mainly related to the hypothetico-deductive model. To address this issue, we have developed a simple and adaptable computer environment that makes use of genetic algorithms (GAs) and symbolic regression to derive many of the basic laws of nature from the data collected by students using the popular physics education technology (PhET) simulations environment. Our proposal enables learners to observe how the order and relationships of mathematical tokens are routinely refined as new data points are added to the simulation setting. This iterative distillation technique can also be augmented with the interplay of dimensional analysis. In contrast with other more sophisticated artificial intelligence patterns, GA fit into the realm of grey box machine learning models. These type of evolutionary algorithms achieve the sought results by evolving mathematical models on each stage in an understandable way, which mimics the way scientific breakthroughs are accomplished (over the course of generations of researchers and based of prior knowledge). By implementing this innovative approach, we can provide students with a more authentic empirical experience that fosters a deeper understanding of the principles of science and scientific discovery. Field tests with students supporting this claim have also been carried out.

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“…Go-Lab is an online learning platform where students can engage in inquiry-based learning in a structured and supportive way (Hovardas et al, 2018). By providing a federation of virtual and remote laboratories and data sets, referred to as "online labs," the Go-Lab platform offers teachers opportunities to embed these online labs in pedagogically structured and inquiry learning spaces (ILSs) (De Jong et al, 2014).…”

Section: The Go-lab Platform With Virtual Labsmentioning

confidence: 99%

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

et al. 2022

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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. We conducted a pre-experimental study with 41 seventhgrade students in Taiwan. The students completed 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 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 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 ndings have implications that instruction design of knowledge integration tasks promotes students' Mendelian genetics conceptual understanding and KI progress.

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Model-Based Inquiry in Computer-Supported Learning Environments: The Case of Go-Lab

Cited by 8 publications

References 61 publications

Nurturing Prospective STEM Teachers' Critical Thinking Skill through Virtual Simulation-Assisted Remote Inquiry in Fourier Transform Courses

Nurturing Prospective STEM Teachers' Critical Thinking Skill through Virtual Simulation-Assisted Remote Inquiry in Fourier Transform Courses

Fostering scientific methods in simulations through symbolic regressions

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

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