Abstract
Over a century since Psychometrics emerged in Psychology, Big Data has risen as a tool for examining vast online data. Educators can effectively blend traditional and new methods to benefit students. By gathering and evaluating various classroom data, instructors can employ several techniques to improve teaching effectiveness and student learning. These techniques include identifying flawed test items using spreadsheets, determining effective assessment methods based on students with regular attendance and participation, and assessing pedagogical techniques enhancing learning, such as sharing vivid stories or integrating concepts across classes. Additionally, educators can analyze predictive models to pinpoint misconceptions, address them, and refine lessons. Quantifying patterns in class data can be used to emphasize the significance of attendance and minimizing distractions. Furthermore, utilizing clustering techniques can help identify student outliers and cater to their specific needs. Lastly, "big data" approaches can be applied to better comprehend and motivate high-potential underachievers, such as by discussing the Law of Diminished Return. These techniques become more reliable with larger class sizes, allowing for impactful education without compromising faculty efforts. By combining data analysis with genuine concern for students, educators can significantly enhance their learning experiences.
Original language | American English |
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State | Published - 2016 |
Event | California State University Symposium on University Teaching - San Jose, United States Duration: Oct 21 2016 → … |
Conference
Conference | California State University Symposium on University Teaching |
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Country/Territory | United States |
City | San Jose |
Period | 10/21/16 → … |
Keywords
- psychometric
- testing & measurement
- big data
Disciplines
- Scholarship of Teaching and Learning
- Data Science
- Quantitative Psychology