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Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman Jan 2021

Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman

Research Collection School Of Computing and Information Systems

Just like most universities around the world, the senior management at Singapore Management University decided to move all courses to a virtual, online, synchronous mode, giving instructors a very short notice period—one week—to make this transition. In this paper, we describe the challenges, practical solutions adopted, and the lessons learnt in rapidly transitioning a face-to-face Master’s degree course in Text Analytics and Applications into a virtual, online, course format that could deliver a quality learning experience.


Effective Teaching Practices In Online Higher Education, Kim Mcmurtry Jan 2016

Effective Teaching Practices In Online Higher Education, Kim Mcmurtry

CCE Theses and Dissertations

In the context of continuing growth in online higher education in the United States, students are struggling to succeed, as evidenced by lower course outcomes and lower retention rates in online courses in comparison with face-to-face courses. The problem identified for investigation is how university instructors can ensure that effective teaching and learning is happening in their online courses. The research questions were:

  1. What are the best practices of effective online teaching in higher education according to current research?
  2. How do exemplary online instructors enact teaching presence in higher education?
  3. What are the best practices of effective online teaching in …


A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti Jan 2015

A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti

CCE Theses and Dissertations

Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …