Course ID:
Course Code & Number
EMT 370
Course Title
Data-Driven Instructional Design in Mathematics Education
Level
BS
Credit Hours/ ECTS Credits
(1+2+0) 2 TEDU Credits, 3 ECTS Credits
Year of Study:
Semester:
Type of Course:
Elective
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite::
Pre-requisites: NONE
Co-requisites: NONE
Catalog Description
Concept of instructional design. Instructional design models. The importance of data in instructional setting. Classroom data gathering strategies. Learning analytics. Educational data mining. Making design decisions based on classroom data for mathematics instruction. Designing mathematics instruction considering classroom data.
Course Objectives
This course aims to make students gain awareness of how to design instruction based on the classroom data. Students will develop a proposal by working on how to make an instructional design considering classroom data and the needs of the learners.
Software Usage
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
1. describe the process of data-driven instructional design,
2. compare different models of instructional design,
3. exemplify the concepts of learning analytics and educational data mining,
4. derive design elements for mathematics instruction based on hypothetical or real classroom data,
5. propose an instructional flow for mathematics instruction based on classroom data.
Learning Activities and Teaching Methods:
Questioning
Reading
Scaffolding/Coaching
Inquiry
Collaborating
Think-Pair-Share
Case Study/Scenarion Analysis
Guest Speakers
Web Searching
Assessment Methods and Criteria:
Test / Exam
Case Studies / Homework
Observation
Presentation (Oral/Poster)
Performance Project (Written, Oral)
Assessment Methods and Criteria Others:
Design Content
Recommended Reading
Required Reading
Grading
Learning Activities and Teaching Methods Others:
Course Coordinator:
Dr. Zerrin Toker
Student Workload:
| Workload | Hrs |
|---|---|
| Course Readings | 3 |
| Hands-on Work | 5 |
| Resource Review | 5 |
| Report on a Topic | 10 |
| Case Study Analysis | 5 |
| Oral Presentation | 5 |
Course & Program Learning Outcome Matching: