MOOC Visual Analytics Tools
Katy Börner (Information and Library Science)
This study will investigate student learning in massive open online courses (MOOCs), developing data mining and visualization tools that render data collected during the MOOCs into actionable insights. This project will empower teachers, students, MOOC platform designers, and researchers to continually improve the implementation of and experiences gained during these courses.
An Inquiry Into Student Purpose And Motivation as Catalysts For Retention
Molly Burke, Anthony Guest-Scott, and Andrew Koke (Student Academic Center)
This study will investigate the efficacy of key aspects of the EDUC-X158 curriculum, examining a wealth of longitudinal data gathered in this course since 2009. EDUC-X158 is a retention course required for University Division students placed on Academic Probation.
Do General or Specific Characteristics of E201 And E202 Affect the Number of Economics Majors?
Paul Graf (Economics)
Class size, instructor selection, class pedagogy, and student preferences and expectations of two Economics courses (E201 & E202) will be examined to determine if enrollment and success in these courses results in a net increase in the number of Economics majors.
Beyond Surveys and Data Mining: Searching for New and Potentially More Useful Indicators of Student Engagement
Daniel Hickey (Counseling and Educational Psychology)
This project will analyze unstructured text found within the artifacts that students generate while enrolled in online and hybrid courses in the School of Education. Analysis will focus on the fine-grained details of productive disciplinary engagement and the relationships of those artifacts to other indicators of engagement and success.
Finding the Keys to Success in Business X201
Kari Johnson (Business)
This study will use analytical data (incoming skills, class activities, graduation rate/job placement) to better understand student success of those enrolled in Business X201-Technology and Business Analytics.
An Investigation of Factors Related to Student Choice of Academic Major at IUB
Adam Maltese (Curriculum and Instruction)
This study will investigate student academic persistence and choice of major using a multimodal strategy involving both existing longitudinal data and a collection of new primary data. The data will be collected at an individual class level in order to understand more broadly how student experiences and performance play a role in higher level decisions they make about major choice and persistence.
Undergraduate Legal System Courses and Where They Fit in the Curriculum for Best Learning Outcomes
Shannon Martin (Journalism)
This study will investigate if student success in legal classes can be correlated to the time in their academic careers that they enroll in particular courses. Using university student course sequencing data to look for correlations of particular courses as a preparation or precursor to legal system courses and student success in those legal system courses.
Learning Analytics in Recreation, Park, and Tourism Studies: The Impact of Two Courses on Student Performance, Major, Selection, and Degree Completion
Rasul Mowatt, Sarah Young, Julia Knapp, and Jared Allsop (Recreation, Park, and Tourism Studies)
This study will use analytical data collected from two core curriculum courses to gain better insights into the RPTS Curriculum and the type of decisions student make. The project will look for correlations between high student achievement in core curriculum courses, success in other RPTS courses, and the factors that lead students to choose RPTS as their major.
The HumAn Learning Project (Humanities, Analytics, & Learning in a Multi-Section General-Education Course)
Jennifer Robinson (Communication and Culture, Anthropology)
This study will investigate the variability of student success across sections of a single large multi-sectional course, seeking patterns in demographics, teaching methods, and learning outcomes that can be used to gain greater student success in future iterations of the course.
Relevant Contributors to Student Success in a Non-Introductory course with a Highly Diverse Student Demographic
Jeffrey Whitmer (Computer Science and Informatics)
This study is concerned with effective teaching and learning in non-introductory courses with very diverse student populations, such as is often found in the School of Informatics and Computing. This study will examine whether eventual student success can be attributed to one or more identifiable factors, including class rank, past student success in prerequisite courses, and past student success in other non-perquisite courses.