A Multiagent System to Support Problem-Based Learning

Fontes, Laysa Mabel de Oliveira; Neto, Francisco Milton Mendes; Pontes, Alexandre Ádames Alves

doi:10.4236/ce.2011.25065

Cited by 7 publications

(2 citation statements)

References 14 publications

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“…The post-test results showed that students could visualize the problem because students were able to understand the meaning of the problems in general after participating in multimodel learning. Visualizing the problem serves to deliver problems from everyday life to the problems contained in the questions, that way, you can visualize the problem, which intends to describe the problem in a complex form (Fontes et al, 2011). This ability serves to see and understand the problems included in the problem by describing certain objects (Foy, 2021).…”

Section: Resultsmentioning

confidence: 99%

The Effectiveness of Multimodel Learning on Linear Motion Topics to Practice Student’s Problem Solving Skills

Agustina¹,

M²,

Haryandi³

et al. 2022

Berk Ilm Pendidik Fis

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Problem-solving ability is important in learning for the achievement of learning objectives. This research aims to describe the effectiveness of multimodal learning on a linear motion to practice students' problem-solving skills. This research is part of developing digital teaching materials on linear motion in a multimodel setting to practice students' problem-solving skills. Using the ADDIE development model over five stages. The subjects of the class trial were 14 students, 11 girls and 3 boys, in class X MIPA 3 of the school in Banjarmasin. The effectiveness is seen from the achievement in multimodel learning in terms of the result of the pre-test and post-test. The results of the N-gain test show that visualizing 0,40 problems in the category, presenting problems into physics concepts 0,88 in the high category, planning the completion of 0,55 in the medium category, carrying out problem-solving 0,80 in the high category, re-examining and evaluating 0,50 is categorized as high. Overall, the gain was 0,62 in the medium category. The research conclusion shows that multimodel learning is effectively used to practice students' problem-solving skills. The implications in education are creating creative and skilled resources and increasing the quality of education to support the future. Suggestions for further research are to increase the number of test subjects, to guide the process of practising problem skills, to distinguish between pre-test and post-test questions, and to carry out the maximum phases of the learning model.

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Section: Resultsmentioning

confidence: 99%

The Effectiveness of Multimodel Learning on Linear Motion Topics to Practice Student’s Problem Solving Skills

Agustina¹,

M²,

Haryandi³

et al. 2022

Berk Ilm Pendidik Fis

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“…Munculnya konsep intelligent agens/ Multi agen systems telah menghimpun berbagai disiplin ilmu dalam upaya membangun sebuah apalikasi terdistribusi, cerdas, dan handal [4]. Pemanfaatan intelligent agen telah banyak dilakukan dalam berbagai bidang, diantaranya untuk membangun sebuah sistem pembelajaran [5,6], desain perilaku pembeli untuk melakukan negosiasi [7], pelayanan kelistrikan industri [8], pengubah preferensi huruf, angka, dan karakter khusus ke dalam struktur database [9].…”

Section: Pendahuluanunclassified

Pemanfaatan Agen Cerdas Untuk Mengukur Prestasi Kerja Pegawai Negeri Sipil (Pns) (The Use of Intelligent Agens for Measure the Working Perfomance of Civil Servants)

Pranolo¹

2015

Telematika

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To implement the governance tasks, professional, responsible, honest, and fair civil servants are needed. It can be attained through a training which is implemented based on the system of working performance and career that focuses on the system of working performance. Therefore, the appraisal of working performance is carried out to evaluate the performance of civil servants for providing guidance to the officials in the evaluation of unit and organization performance. This study aims to make intelligent agens design, so that the working units and governmental organizations can do evaluation based on the self-evaluation of their employees' working performance. It refers to the government regulation number 46 year 2011, that the appraisal of the civil servants' working performance consists of Employee's Work Goal (EWG) and Work Behavior (WB) with the percentages for each are 60% and 40%. The intelligent agens that can be formed from this case consist of 1) Agen-evaluator who provides the feed back of working performance progress, 2) Agen-work planner who contributes in providing recommendation of jobs which are apropriate with the civil servants whose working performance is still low, and 3) Agen-record-of-performance who contribute in recording the performance of Civil Servants.

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