Development of An Android-Based Physics E-Book with A Scientific Approach to Improve The Learning Outcomes of Class X High School Students on Impulse and Momentum Materials

Ndoa, Yohana Atwina Aspiranti; Anastasia, D P; Jumadi, J

doi:10.15294/jpfi.v18i2.30824

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Previous researchers could predict student learning achievement with an accuracy of up to 80% using these two algorithms. Teachers can use this information as feedback that can be given to students to support student learning (Atmam & Mufit, 2023;Ndoa & Anastasia, 2022). According to the constructivist approach, effective physics learning provides students with independent learning, which is supported by the teacher's activeness in monitoring learning, which the results of ML predictions can generate.…”

Section: Introductionmentioning

confidence: 99%

Predicting Physics Students’ Achievement Using In-Class Assessment Data: A Comparison of Two Machine Learning Models

Santoso,

Santosa,

Istiyono

et al. 2023

PERJ

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Data is the primary source to scaffold physics teaching and learning for teachers and students, mainly reported through in-class assessment. Machine learning (ML) is an axis of artificial intelligence (AI) study that immensely attracts the development of physics education research (PER). ML is built to predict students’ learning that can support students’ success in an effective physics achievement. In this paper, two ML algorithms, logistic regression and random forest, were trained and compared to predict students’ achievement in high school physics (N = 197). Data on students’ achievement was harvested from in-class assessments administered by a physics teacher regarding knowledge (cognitive) and psychomotor during the 2020/2021 academic year. Three assessment points of knowledge and psychomotor were employed to predict students’ achievement on a dichotomous scale on the final term examination. Combining in-class assessment of knowledge and psychomotor, we could discover the plausible performance of students’ achievement prediction using the two algorithms. Knowledge assessment was a determinant in predicting high school physics students’ achievement. Findings reported by this paper recommended open room for the implementation of ML for educational practice and its potential contribution to supporting physics teaching and learning.

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Section: Introductionmentioning

confidence: 99%

Predicting Physics Students’ Achievement Using In-Class Assessment Data: A Comparison of Two Machine Learning Models

Santoso,

Santosa,

Istiyono

et al. 2023

PERJ

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“…Creative ideas are needed to be able to solve good problems. Organizational skills are owned by individuals who have high creativity (Ndoa & Anastasia, 2022). Within the organization, individuals are encouraged try to think ahead and challenged to come up with innovative ideas that are expected to be utilized by society (Haris Odja et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Fluidmistar Media in Inquiry to Improve the Creative Thinking Skills of Senior High School Students

Susilawati,

Anwar

2023

phen

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Learning media an important role in supporting the learning process as a tool for students to gain mastery of the material. This study aims to produce valid fluidmistar media and analyze the increase in students' creative thinking skill after using fluidmistar learning media. Research and development is a method specifically using the ADDIE development model. The data collection technique used was a test of creative thinking skills and a student response questionnaire. The results of the expert's assessment stated that fluidmistar media was feasible to use improve creative thinking skills through inquiry learning. The implementation of fluidmistar media in inquiry learning was applied to students of senior high school in Sragen, Central Java with a total sample of 58 students. Student responses to the Fluidmistar learning media obtained good category. The results of students' positive responses indicate that the developed media to improve students' creative thinking skill and positive responses. The increase in creative thinking skill can be seen based on the pretest and posttest score tested through the N-gain test obtained at 0.74 in the high category. Fluidmistar learning media is suitable for use in inquiry learning to improve students' creative thinking skills on dynamic fluid material.

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Development of An Android-Based Physics E-Book with A Scientific Approach to Improve The Learning Outcomes of Class X High School Students on Impulse and Momentum Materials

Cited by 2 publications

References 12 publications

Predicting Physics Students’ Achievement Using In-Class Assessment Data: A Comparison of Two Machine Learning Models

Predicting Physics Students’ Achievement Using In-Class Assessment Data: A Comparison of Two Machine Learning Models

Fluidmistar Media in Inquiry to Improve the Creative Thinking Skills of Senior High School Students

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