Improving students' critical thinking ability through model argument driven inquiry (ADI) integrated STEM

Suganda, Tomy; Parno, Parno; Sunaryono, Sunaryono; Latifah, Eny; Yuliati, Lia

doi:10.1063/5.0112514

Cited by 2 publications

(2 citation statements)

References 35 publications

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“…A decrease in academic motivation can be seen from the presence of burnout, lack of enthusiasm and desire to excel, and decreased level of information absorbed to a reduction in the ability of individual students to demonstrate learning (Hidajat et al, 2020;Hysenbegasi et al, 2005;Setiyoaji et al, 2021). Various kinds of treatments for student productivity and academic quality have been proposed in previous studies (Parno et al, 2021;Setiyoaji et al, 2021;Suganda et al, 2023). However, a comprehensive response to mental health issues is still much needed (Strunk et al, 2021;World Health Organization, 2017).…”

Section: Introductionmentioning

confidence: 99%

Optimization of Depression Level Detection Based on Noninvasive Parameters with Artificial Neural Network

E.,

Wisesa,

Pramono

et al. 2023

JOWUA

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We optimized the measurement of depression levels by developing an instrument that processes four physical parameters non-invasively with an Artificial Neural Network (ANN). High-accuracy detection instruments help establish a diagnosis to realize early and appropriate prevention and treatment of depression. Depression among students tends to increase, which has an impact on reducing productivity and even attempting suicide. It can reduce the quality and quantity of the productive age generation. The selection of non-invasive physical parameters, namely heart rate, hours of sleep, respiratory rate, and blood oxygen, considers practical aspects for the examiner and the subject examined. This research uses an exploratory method to develop an ANN-based tool for detecting student depression levels. The ANN-based Depression Detector (dANN) input layer harvests data from measurements of the four parameters. Then, the ANN hidden layer processes and studies the data in depth to present five levels of depression in the output layer. Learning results using Loss Graphs show that dANN reduces prediction errors or training iterations at Epochs greater than 130 or offers high accuracy after reaching Epoch 130. DANN prioritized high accuracy in practical measurements. dANN has the potential to be further developed by integrating psychological parameter data, considering that depression is multifactorial. The result of classification reported a precision of 1.0. This felicitating value presents the success of learning and training on dANN. Furthermore, dANN will be built on a web basis to improve performance by implementing an expert system.

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Section: Introductionmentioning

confidence: 99%

Optimization of Depression Level Detection Based on Noninvasive Parameters with Artificial Neural Network

E.,

Wisesa,

Pramono

et al. 2023

JOWUA

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“…With these several aspects, individuals are expected to be able to solve problems easily (Agung et al, 2022;Anggraini et al, 2022). Suganda et al (2023) stated that based on the research he had conducted, the STEMintegrated ADI model had a significant influence on improving students' critical thinking skills. While in this study, the STEM-integrated ADI model will be developed to train students' argumentation skills and self-efficacy.…”

Section: Introductionmentioning

confidence: 99%

Validity of Student Worksheets Based on Model Argument Driven Inquiry Integrated by STEM to Train Students' Argumentation Ability and Self-Efficacy in Chemical Equilibrium Material

Hikmah

Tukiran

Nasrudin

2023

IJORER Int. J. Recent Educ. Res.

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Objective: One of the teaching materials that can increase students' interest and learning motivation is student worksheet with an interesting learning model. This study aims to: (1) train students' argumentation abilities when they want to express their opinions regarding chemical equilibrium material and (2) train students' self-efficacy by bringing opinions related to equilibrium material. Method: The research method refers to the 4D model, namely definition, design, development, and deployment. However, it is only limited to the third stage. The data collection technique used the validation method by three validators, namely two chemistry lecturers and one high school chemistry teacher. The instruments used to assess the validity of the student worksheet are content validity sheets and construct validity sheets. The data obtained is then processed using the agreement percentage formula. Results: student worksheet 1, student worksheet 2, and student worksheet 3 are feasible in terms of content and construction validity with very valid categories. This is evidenced by the agreement percentage value on each student worksheet which is above 75%. Novelty: student worksheet modeled on STEM-integrated ADI will be developed to train students' argumentation skills and self-efficacy. This novelty can be assessed as being able to provide: (1) solutions related to students' interest in ideas on chemical equilibrium material, especially the sub-factors of shifting factors towards chemical equilibrium and (2) being able to increase students' confidence when conveying their ideas or other actions.

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Improving students' critical thinking ability through model argument driven inquiry (ADI) integrated STEM

Cited by 2 publications

References 35 publications

Optimization of Depression Level Detection Based on Noninvasive Parameters with Artificial Neural Network

Optimization of Depression Level Detection Based on Noninvasive Parameters with Artificial Neural Network

Validity of Student Worksheets Based on Model Argument Driven Inquiry Integrated by STEM to Train Students' Argumentation Ability and Self-Efficacy in Chemical Equilibrium Material

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