PENERAPAN MODEL ADAPTIF DALAM RANCANG BANGUN SISTEM KUIS ONLINE

Makalah ini membahas sebuah sistem kuis berbasis web dengan fitur adaptif yang ditambahkan. Sistem kuis adaptif ini menjadi lebih personalisasi karena model pertanyaan yang disajikan secara khusus dirancang bagi siswa sesuai dengan tingkat kemahiran mereka. Siswa akan lebih mengenal kekuatan dan kelemahan dalam proses belajar mereka karena mereka tidak akan menuju ke tingkat kesulitan yang lebihtinggi jika mereka tidak memenuhi nilai yang dipersyaratkan pada tingkat tertentu. Makalah ini fokus pada komponen utama fitur adaptif dan teknik untuk melaksanakan komponen adaptif tersebut. Sebuah studi perbandingan antara sistem adaptif saat ini dilakukan untuk mengidentifikasi komponen adaptif yangditerapkan dan teknik untuk menerapkan komponen adaptif. Hasil studi banding menjadi dasar untuk mengembangkan sistem kuis adaptif ini. Sistem kuis adaptif ini terdiri dari tiga komponen utama: student model, domain model dan adaptation model. Student model menggambarkan pengetahuan siswa, model domain merupakan domain mengajar atau representasi dari student model, sedangkan adaptation model terdiri dari satu sekumpulan aturan yang mendefinisikan aksi pengguna. Teknik stereotype dan overlaymodel diterapkan untuk student model, semantic network diterapkan pada domain model dan 'IF-THEN' rule diterapkan pada adaptation model. Sistem kuis adaptif ini menjadi sebuah sistem penilaian siswa berdasarkan kemampuan, pengetahuan dan preferensi dari masing-masing peserta didik.Kata kunci : Kuis online, adaptif, student model, domain model, adaptation mode

An intelligent tutoring system for student guidance in web-based courses

In this study, an intelligent agent to guide students throughout the course material in the internet is defined. The agent will help students to study and learn the concepts in the course by giving navigational support according to their knowledge level. It uses simplified prerequisite graph model as domain model and simplified overlay model for modeling student. The system adapts the links in the contents page to help students for easy navigation in the course content. In link-level adaptation hiding and annotation technologies which effectively support gradual learning of the learning space are used

An adaptive domain-independent agents-based tutor for Web-based supplemental learning environments

Thesis (Ph. D .)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.Includes bibliographical references (p. 170-185).The Physics Interactive Video Tutor (PIVoT) is a Web-based multimedia resource for college-level Newtonian mechanics. The Personal Tutor (PT) is an intelligent tutoring system (ITS) integrated into PIVoT, assisting students and teachers in navigating through, understanding, and assessing PIVoT's educational media. PT is adaptive in that it personalizes its functionality to the preferences of its user. The combined PIVoT / PT system was designed to be domain-independent with respect to the style of pedagogy, models of user learning, and instructional algorithms. Thus, this design is easily adapted for use beyond the tested domain of introductory college physics. PT is designed in the object-oriented paradigm, building upon the recent work in multi-agent systems (MAS). This agents-based approach, along with innovations in negotiating student-agent control and communication, allow current and future competing pedagogical strategies and cognitive theories to coexist harmoniously. New efficient, domain-independent techniques for discovering, updating, and presenting students' contextual interests improve information retrieval and site navigation. Unlike other computer-based instruction systems used as a tool for primary learning and assessment, PIVoT is used as a supplementary resource focusing on providing formative assessment to both student and educator alike. The PIVoT / PT system leverages reusability and system independence, two often-overlooked strengths of agent-based approaches to intelligent tutoring systems. Combined, PIVoT and the Personal Tutor provide an effective proving ground for innovations in intelligent tutoring system design that also reduces the cost of making such software.by Steven Niemczyk.Ph.D