Description of Student Responses Toward the Implementation of Problem-Based Learning Model in Physics Learning

Tanti, Tanti; Kurniawan, Dwi Agus; Sukarni, Weni; Erika, Erika; Hoyi, Roro

doi:10.26737/jipf.v6i1.1787

Cited by 13 publications

(12 citation statements)

References 24 publications

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“…This study used a mixed method with an explanatory model, the variables in the form of students' perceptions of the mathematical physics e-module on the dual integral material. Mixed method explanatory model is a mixture of research methods with quantitative and qualitative research sequentially (Tanti et al, 2021). In the first stage, quantitative data collection was carried out followed by the second stage, namely, qualitative data collection.…”

Section: Methodsmentioning

confidence: 99%

“…In quantitative research, the sample used is analyzed systematically and the results are in the form of numbers. Collecting quantitative data using a survey method which is intended to determine in general the characteristics of the sample under study (Tanti et al, 2021). Strengthening and completing quantitative data can be done using qualitative data.…”

Section: Methodsmentioning

confidence: 99%

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Students' Perceptions of Mathematical Physics E-Module on Multiple Integral Material

Astalini

Kurniawan

Chen

2021

j.of education technology

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Mathematical physics is often considered a very difficult subject to study, one of the reasons that makes this happen is the lack of learning media that supports students. In addition, most of the existing media are in foreign languages, so in this case we need an Indonesian language learning media, namely the mathematical physics e-module on dual integral material. This study aims to see the level of students' perceptions of the mathematics physics e-module on the dual integral material that has been made. The approach of this study uses a mixed method with an explanatory model. The sampling technique in this research was purposive sampling with 68 research subjects active physics education students who contracted Mathematics Physics courses. The instrument used in this study was a student perception questionnaire with 15 questions and an interview sheet with 10 questions.. The data analysis used in this research is descriptive statistics. The results of physics education students' perceptions of the mathematics physics e-module of multiple internal material were categorized as good with a percentage of 66.17% and in the very good category with a percentage of 33.83%. From the results it can be seen that the mathematical physics e-module on dual integral material can support the learning process and increase student motivation.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Students' Perceptions of Mathematical Physics E-Module on Multiple Integral Material

Astalini

Kurniawan

Chen

2021

j.of education technology

Self Cite

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“…In this instance, students are not given learning techniques that allow them to comprehend how to learn not only from the teacher, think, and motivate themselves. This shows that without applying learning methods will affect the quality of student learning outcomes (Dupri et al, 2020;Marzuki & Basariah, 2017;Tanti et al, 2021). There are disparities in the learning outcomes of pupils who use the method vs those who use conventional methods (Armiyanti, 2019;Haji et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

The Effect of Internet Use on Improving Student Learning Outcomes

Prasetyo

Nurhidayah

2021

J. Educ. Technol.

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Students have difficulty in learning, so that it has an impact on low learning outcomes. The low student learning outcomes can be caused by the quality of learning, one of which is the lack of learning reference sources. The purpose of this study was analyze improvement of students' Biology learning outcomes before and after the application of internet use. This type of research is a quasi-experimental design through the Nonequivalent Control Group Design. The subjects in this study were students of class IX, which in this study used two classes, namely the control class and the experimental class. Learning in the control class is the usual lecture method, while in the experimental class it is done by applying the method of using the internet. The acquisition of learning outcomes data using the learning outcomes test (pretest-posttest). The hypothesis test using covariance analysis aims to determine whether there is an effect of the independent variable on the dependent variable. The results of the data obtained indicate that the effect of using the internet can improve student learning outcomes. The results of inferential statistical analysis obtained the value of Sig.count 0.000 with = 0.05. The results of the analysis indicate that the value of Sig.count is greater than (0.000 > 0.05) so Ho is rejected and H1 is accepted. So it can be concluded that in the learning process by utilizing the internet as a complement to conventional learning can improve student learning outcomes. Thus the internet as a learning resource can improve learning outcomes.

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“…(1) Description-Based Learning [18]. In a data area, we describe a concrete example, find the main factors associated with the concrete example, and finally perform the process of forming a generalized concept.…”

Section: Machine Learning Eory Machine Learning Breeds Strong Vitalitymentioning

confidence: 99%

A Gaussian Process Classification and Target Recognition Algorithm for SAR Images

Yang

Zhang

2022

Scientific Programming

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Synthetic aperture Radar (SAR) uses the relative movement of the Radar and the target to pick up echoes of the detected area and image it. In contrast to optical imaging, SAR imaging systems are not affected by weather and time and can detect targets in harsh conditions. Therefore, the SAR image has important application value in military and civilian purposes. This paper introduces the classification of Gaussian process. Gaussian process classification is a probabilistic classification algorithm based on Bass frame. This is a complete probability expression. Based on Gaussian process and SAR data, Gaussian process classification algorithm for SAR images is studied in this paper. In this paper, we introduce the basic principle of Gaussian process, briefly analyze the basic theory of classification and the characteristics of SAR images, provide the evaluation index system of image classification, and give the SAR classification model of Gaussian process. Taking Laplace approximation as an example, several classification algorithms are introduced directly. Based on the two classifications, we propose an indirect multipurpose classification method and a multifunction classification method for two-pair two-Gaussian processes. The SAR image algorithm based on the two categories is relatively simple and achieves certain results.

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Description of Student Responses Toward the Implementation of Problem-Based Learning Model in Physics Learning

Cited by 13 publications

References 24 publications

Students' Perceptions of Mathematical Physics E-Module on Multiple Integral Material

Students' Perceptions of Mathematical Physics E-Module on Multiple Integral Material

The Effect of Internet Use on Improving Student Learning Outcomes

A Gaussian Process Classification and Target Recognition Algorithm for SAR Images

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