Combining Fuzzy Set – Simple Additive Weight and Comparing With Grey Relational Analysis For Student’s Competency Assessment In The Industrial 4.0

Cường, Bùi Công; Nghiem, Thi-Lich; Ha, Dinh Thi

doi:10.1109/kse.2018.8573321

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…(1) rij adalah rating kinerja ternormalisasi dari alternatif Ai pada atribut Cj; i=1,2,...,m dan j=1,2,...,n. Nilai preferensi untuk setiap alternatif (Vi) diberikan sebagai berikut [17], [18], [19]: Konsep ANEKA pada dasarnya merupakan kependekan dari kata "Akutabilitas", "Nasionalisme", "Etika Publik", "Komitmen Mutu", dan "Anti Korupsi" [20], [21]. ANEKA merupakan suatu nilai-nilai yang harus mampu diinternalisasikan secara baik dan optimal oleh para pegawai negeri sipil dalam melaksanakan tugasnya, sehingga dapat menunjukkan tingkat profesionalisme mereka.…”

Section: ∑(Jawaban X Bobot Tiap Pilihan) Persentase = ---------------unclassified

Pengembangan Model Evaluasi Stake Berbasis ANEKA-Tri Hita Karana dengan Pengkalkulasian SAW dalam Penentuan Aspek-aspek Prioritas Perbaikan Mutu Belajar dan Karakter Siswa

Divayana

2020

JEPIN

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Model evaluasi yang dapat digunakan secara akurat untuk mengevaluasi mutu belajar dan karakter siswa pada SMK TI dan mampu memberikan rekomendasi yang tepat dengan menunjukkan aspek-aspek prioritas yang perlu disempurnakan, merupakan suatu inovasi baru yang menjadi kebutuhan dunia pendidikan di era revolusi industri 4.0 saat ini. Penelitian ini dilaksanakan dengan tujuan utama untuk mengetahui bentuk rancangan dari model evaluasi pendidikan yang menggabungkan model Stake, konsep ANEKA, konsep Tri Hita Karana dan metode SAW (Simple Additive Weighting) sebagai terobosan untuk menjawab kebutuhan dunia pendidikan terkait inovasi baru dalam pengembangan model evaluasi pendidikan. Metode yang digunakan dalam mengembangkan model evaluasi ini adalah metode Research & Development (R&D) dengan desain Borg and Gall. Subjek yang dilibatkan pada uji coba rancangan dan simulasi perhitungan SAW dalam penelitian ini sebanyak dua pakar pendidikan dan dua pakar informatika. Alat yang digunakan dalam pengumpulan data dalam penelitian ini berupa kuesioner dan foto dokumentasi. Teknik deskriptif kuantitatif digunakan untuk mengenalisis data yang terkumpul dalam penelitian ini. Hasil penelitian ini menunjukkan persentase efektivitas rancangan model evaluasi sebesar 89% sehingga dapat dikategorikan baik dan tidak perlu dilakukan revisi major jika ditinjau dari pengkonversian tingkat pencapaian efektivitas dengan skala lima.

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Section: ∑(Jawaban X Bobot Tiap Pilihan) Persentase = ---------------unclassified

Pengembangan Model Evaluasi Stake Berbasis ANEKA-Tri Hita Karana dengan Pengkalkulasian SAW dalam Penentuan Aspek-aspek Prioritas Perbaikan Mutu Belajar dan Karakter Siswa

Divayana

2020

JEPIN

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“…In contrast, the linguistic approach premise is that neither the students' grades nor the relationship importance can be precisely expressed with numbers. For instance, [25]- [28] propose assessment procedures based on fuzzy linguistic logic to aggregate students' grades and relationship importance expressed in natural language (e.g., ''learning outcome LO is poorly achieved'' and ''LO is essential for competency C'', respectively).…”

Section: Related Workmentioning

confidence: 99%

Automated Assessment and Monitoring Support for Competency-Based Courses

et al. 2019

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Competency-based education is becoming increasingly adopted by higher education institutions all over the world. This paper presents a framework that assists instructors in this pedagogical paradigm and its corresponding open-source implementation. The framework supports the formal definition of competency assessment models and the students' evaluation under these models. It also provides distinct learning analytics for identifying course shortcomings and validating corrective actions instructors have introduced in a course. Finally, this paper reports the benefits of applying our framework to an engineering course at the Pontifical Catholic University, Valparaíso, Chile for three years.INDEX TERMS Competency-based education, course assessment, course monitoring, learning outcome.

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“…As mentioned earlier, the knowledge of the users on the subject seems to be the most important characteristic for error diagnosis in most AEHSs. Almost all adaptive presentation techniques, e.g., fuzzy weights [3,4], artificial neural networks [5,6], multiple-criteria decision analysis [7,8], are based on user knowledge as the main source of personalization. User knowledge is a variable for each user.…”

Section: Introductionmentioning

confidence: 99%

A Cognitive Diagnostic Module Based on the Repair Theory for a Personalized User Experience in E-Learning Software

2021

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This paper presents a novel cognitive diagnostic module which is incorporated in e-learning software for the tutoring of the markup language HTML. The system is responsible for detecting the learners’ cognitive bugs and delivering personalized guidance. The novelty of this approach is that it is based on the Repair theory that incorporates additional features, such as student negligence and test completion times, in its diagnostic mechanism; also, it employs a recommender module that suggests students optimal learning paths based on their misconceptions using descriptive test feedback and adaptability of learning content. Considering the Repair theory, the diagnostic mechanism uses a library of error correction rules to explain the cause of errors observed by the student during the assessment. This library covers common errors, creating a hypothesis space in that way. Therefore, the test items are expanded, so that they belong to the hypothesis space. Both the system and the cognitive diagnostic tool were evaluated with promising results, showing that they offer a personalized experience to learners.

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Combining Fuzzy Set – Simple Additive Weight and Comparing With Grey Relational Analysis For Student’s Competency Assessment In The Industrial 4.0

Cited by 5 publications

References 10 publications

Pengembangan Model Evaluasi Stake Berbasis ANEKA-Tri Hita Karana dengan Pengkalkulasian SAW dalam Penentuan Aspek-aspek Prioritas Perbaikan Mutu Belajar dan Karakter Siswa

Pengembangan Model Evaluasi Stake Berbasis ANEKA-Tri Hita Karana dengan Pengkalkulasian SAW dalam Penentuan Aspek-aspek Prioritas Perbaikan Mutu Belajar dan Karakter Siswa

Automated Assessment and Monitoring Support for Competency-Based Courses

A Cognitive Diagnostic Module Based on the Repair Theory for a Personalized User Experience in E-Learning Software

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