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Educational Software
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CC BY-NC-SA
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MAIN AIMS OF THE MODULE: To achieve an understanding and practical experience of key principles, methods and theories in the area of educational software.
LEARNING OUTCOMES FOR THE MODULE: The module provides opportunities for students to develop and demonstrate knowledge and understanding, qualities, skills and other attributes in the following areas:
1) Obtain understand of major learning principles, theories, and approaches
2. Identify key factors of successful educational software design and deployment.
3) Apply theories, principles, and approached into an appropriate design of educational software system.
4) Establish an appreciation of state-of-art developments in the area of educational software design.
MAIN TOPICS OF STUDY: The main topics of study considered in light of the above learning outcomes are: ‰ Educational Principles Design of educational software such as electronic instruction manuals, serious gaming, VR training, drills, and tutor agents and tutorials ‰Educational software for specific learners such as children, elderly, mentally or physically challenged individuals ‰CEvaluation of education software.

Subject:
Computer Science
Information Technology
Material Type:
Assessment
Homework/Assignment
Lecture
Lecture Notes
Lesson Plan
Reading
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Dr.Ir. W.P. Brinkman
Date Added:
08/13/2020
Empirical Research Methods
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CC BY-NC-SA
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The main topics of study considered in light of the above learning outcomes are:Research philosophy (e.g. positivism, empiricism, naturalism)Formulating empirical research questions and conceptual research modelsCausality effects and relationshipsValidity and ReliabilityScales of measurement (e.g. nominal, ordinal, interval, ratio)Sampling methods (e.g. experiment, survey, observations) and measure instruments (e.g. Likert scales, semantic differential, event versus time sampling)Experimental design (e.g. within and between-subjects, factorial design, counter-balancing, Latin square)Biases in empirical research approaches (e.g. confounding variables, statistical power)Data preparation (e.g. standardization of data, reliability analysis, Inter-rater reliability)Hypothesis testing, t-test, (M)ANOVA, correlation, regression analysisNon-parametric approaches to data analysis

Subject:
Engineering
Material Type:
Lecture Notes
Reading
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Dr.Ir. W.P. Brinkman
Date Added:
08/13/2020