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Learning Analytics & Educational Data Mining for Inquiry-Based Learning

Learning Analytics & Educational Data Mining for Inquiry-Based Learning

Trending PhD Thesis on Learning Analytics & Educational Data Mining for Inquiry-Based Learning

Research Area:  Data Mining

Abstract:

   The growing interest in recent years towards Learning Analytics (LA) and Educational Data Mining (EDM) has motivated the development of novel approaches and advancements in educational settings. The wide variety of research and practice in this context has enforced important possibilities and applications from adaptation and rationalization of Technology Enhanced Learning (TEL) systems to the improvement of instructional design and pedagogy choices based on students needs.
   s. LA and EDM play an important role in enhancing learning processes by offering innovative applications of analytics methods. This leads to the knowledge discovery about the learning processes, and development and integration of more personalized, adaptive, and interactive educational environments. Inquiry-based learning (IBL) environments are considered as promising TEL environments to increase the knowledge and skills of learners. IBL focuses on con-texts where learners are meant to discover knowledge rather than passively memorizing the concepts. LA and EDM are gaining attention in IBL contexts as a way to help facilitate learning and improve learning achievements of the students.
   In this thesis, we aim to present novel applications of LA and EDM focused on IBL contexts. In particular, we aim to address what analytics methods can quantify the learning processes in an IBL cycle. We consider a learner-centered inquiry cycle as a structure to explain our objectives regarding three educational contexts.
   This cycle comprises of three main learning phases: 1 - conceptualization (generating hypothesis and question),2 - investigation and discovery, 3 - conclusion and reflection. We focus on each phase in a different educational context through the application of LA and EDM.

Name of the Researcher:  Mehrnoosh Vahdat

Name of the Supervisor(s):  Remi Brochenin

Year of Completion:  2017

University:  Eindhoven University

Thesis Link:   Home Page Url