In support of Indiana University's Bicentennial Strategic Plan, the Center for Learning Analytics and Student Success (CLASS) advances the widespread use of big data and student learning analytics, empowering faculty to conduct actionable scholarly research through the systematic collection, exploration, and analysis of data describing students, their observable activities, and outcomes. CLASS organizes and supports professional learning communities, whose participants collaborate with Bloomington Assessment and Research, the Center for Innovative Teaching and Learning, and the Bay View Alliance.
Teaching, learning, and student success
Big data, predictive modeling, and learning analytics have rapidly emerged as some of the most robust and promising methods for ensuring that all students achieve their highest potential during their college years.
Learning Analytics Fellows
The Student Learning Analytics Fellows Program funds faculty-driven research projects that use learning analytics to foster student engagement, retention, and success at Indiana University. Participating Fellows use various methods to study students as learners through the systematic collection, exploration, and analysis of data describing students, their observable activities, and outcomes.
Contact George Rehrey
Using Analytics to Evaluate Influences on Student Learning Outcomes in a GenEd Science Course (G131, Oceans & Our Global Environment): Phase II of an Analytics Approach Simon Brassell (Geological Sciences)
This project seeks to continue to utilize analytics on student demographics and grade records in combination with data on their performance in the GenEd NMS class G131 “Oceans and Our Global Environment” to assess how performance in the class and its range of assignments may be related to specific student characteristics.
Evaluating the Teaching Effectiveness of Principles of Microeconomics Instruction at IU Bloomington Campus Relative to Other Institutions Gerhard Glomm and Paul Graf (Economics)
The aim of this study is to investigate more thoroughly if or to what extent students who are transferring in credit to IU for E201 are (in)adequately prepared for higher level courses such as E321.
Determinants of Student Attrition Michael Kaganovich (Economics)
The proposed research will focus on the factors behind IU students’ decisions to make substantial changes in their studies at IU: to discontinue enrollment altogether (i.e., to drop out) or to switch from one major to another.
How Does the Sequencing of Major Courses Influence Student Success? Jie Li (Business)
It has been noted that a large number of students wait until their senior year to take their major courses. As a result, they get an unbalanced course load, lose the benefit of knowledge scaffolding built into the proper sequencing of the courses. This research seeks to understand the severity of the problem.
Evaluating Student Performance in C118 and N330 Based on Prior Academic Performance Meghan Porter (Chemistry)
This Phase I project seeks to examine the student-perceived differences between C118: Principles of Chemistry and Biochemistry II and N330: Intermediate Inorganic Chemistry, both second-semester general chemistry courses offered by the Department of Chemistry at Indiana University.
Learning Analytics for Students Majoring in Healthcare Management and Policy Terri Renner (SPEA)
Many students enrolled in SPEA’s Healthcare Management and Policy degree program (HMP) struggle in our quantitative courses in financial management and economics. SPEA is revisiting the issues of appropriate admission criteria and prerequisite courses, as well as how to address our students’ overall difficulty with quantitative courses. My research question is as follows: What is the profile of the student who is successful (grade of “C” or better) in healthcare finance and economics courses?
Mitigating Grade Surprise: A Study of Students’ Grade Expectations Using Learning Analytics and Assignment Performance in General Education Courses at Indiana University Jennifer Robinson, Jill Robinson, John Arthos, Nina Onesti, Logan Paul, Chung-chieh Shan and Sam Tobin-Hochstadt (Anthropology, Chemistry, English, Informatics and Computer Science)
This project investigates grade surprise—the unrealistic expectations students have for their grades, the subsequent consequences of surprise, and the factors that can mitigate it—in large classes across the general education curriculum.
Evaluating and Visualizing the Impact of Language Requirement and Abroad Programs on Students’ Performance, Retention, and Major Olga Scrivner and Julie Madewell (Spanish and Portuguese)
This project aims to (1) analyze the impact of the GenEd courses on students’ overall performance and their career choice and (2) to develop analytical tools to measure students’ trajectory from high school to graduation.
Examining the Consequential Validity of the New Online English Placement Exam Sun-Young Shin (Second Language Studies)
This study will seek to understand how ELIP instruction can directly affect academic English performance by utilizing a dataset of pre- and post-instruction writing and speaking scores. These datasets will allow this study to evaluate the effectiveness of ELIP courses as a result of the IAET by exploring how students who are placed into ELIP courses perform differently at various measures of academic success.
Evaluating the Effectiveness of Integrated Information Literacy Instruction on Student Outcomes in the English W131 Multilingual Curriculum Katherine Silvester and Andrew Asher (Anthropology)
Using a combination of institutional records, measures of student success and achievement, and a rubric-based assessment of students’ research-oriented course assignments, this study aims to identify the kinds of information literacy instruction that are most effective, the times during a course or curriculum when instruction has the greatest impact, and the characteristics of students that benefit most from instructional interventions.
Using Analytics to Evaluate Influences on Student’s Grades in an Introductory Nutrition Course (N231-Human Nutrition) Krisha Thiagarajah (School of Public Health)
This study aims to understand the students whom take the course, Human Nutrition N231, and to establish the important characterisitics that help and/or hinder students in this course.
Tracking Student Movement in the SPHB through Learning Analytics Sarah Young, Jarod Allsop, William Ramos, Donetta Cothran, Maresa Murray and Dohyun Lee (Recreation, Park, and Tourism Studies)
An area of concern has been the documented decrease in the number of undergraduate majors in the legacy departments.. Attached to all of this is a concern over credit hour generation and underlying issues that may be taking place with student understanding of the new school message and perhaps quality related factors. As a means to begin understanding this phenomenon, this study is designed to examine variables associated with those undergraduate students who matriculated into the SPHB but then transitioned out.
Measuring the Impact of Information Literacy Instruction on Assignment-Level Learning Outcomes
Andrew Asher (Library Academic Services)
Evaluating the impact of library-provided information literacy instruction on students' learning outcomes through an understanding of the types of information literacy instruction that are most effective, the times during a student's course of study that instruction is most impactful, and the types of students that most benefit from instructional interventions.
Evaluating and Optimizing Homework and Quizzes to Increase Learning Outcomes in the Information Visualization MOOC
Katy Börner (Intelligent Systems Engineering)
As part of efforts to update course materials, instructors need to evaluate the impact of assessment quizzes and hands-on homework activities on student engagement and performance to improve instructional materials an learning outcomes. This will be the focus of a graduate level course entitled Information Visualization MOOC (IVMOOC).
Using Analytics to Evaluate Influences on Student Learning Outcomes in a GenEdScience Course (G131, Oceans & Our Global Environment)
Simon Brassell (Geological Sciences)
Utilizing analytics on student demographics and grade records in combination with data on their performance in the G131 to assess how performance in the class and its range of assignments may be related to specific student characteristics which will be used to identify modifications to improve the learning outcomes of students.
Evaluating the Impact of the Intensive English Program on Student Success at IU
Leslie Gabriele (Second Language Studies)
This study will evaluate the impact of the Intensive English Program (IEP), an academic English language preparation program for pre-matriculated international students, on students future academic success using external measures such as University/College admission rates and student progress through their programs of study at Indiana University GPAs, retention rates, and graduation rates.
Evaluating the Teaching Effectiveness of Principles of Microeconomics Instruction at the IU Bloomington Campus Relative to Other Institutions
Paul Graf, Gerhard Glomm (Economics)
As community colleges and Research 1 Universities like IU employ different pedagogies, e.g. different class sizes and different teaching personnel, teaching effectiveness may well vary across these two institutions. This project will focus on the teaching effectiveness in Microeconomics courses.
The Factors of Differential Grading Standards across Academic Units
Michael Kaganovich (Economics)
As the second phase of the project Determinants of Students' Choices of Undergraduate Majors and Programs' Strategies, the long-term agenda of this research is to identify factors contributing to IU undergraduate students' choices of their major concentrations, and especially to infer the actions and policies of major programs in effecting those student decisions.
The Factors to and Impact of K303 Success
Jie Li (Business)
A further study on the factors that might have certain predicting power of student performance in K303 and the impact of the course on students' later academic performance, major selection and career development outcomes.
Learning Analytics for Students Majoring in Healthcare Management and Policy
Terri Renner (SPEA)
What is the profile of the student who is successful (grade of "C" or better) in healthcare finance and economics courses? The ultimate goal is to use this information to identify students early on who may struggle in these courses and therefore offer early intervention options, such as appropriate prerequisite courses, a SPEA "math camp", or online math "Modules" in conjunction with appropriate tutoring.
Human Expertise, Analytics, & Student Learning in Multi-Section General-Education Courses at Indiana University
Jennifer Robinson, John Arthos, and Jill Robinson (Anthropology, English, Chemistry)
The HumAn Learning Project uses learning analytics to triangulate on strategies for fostering student success in multi-section, general education courses. Phase 3, proposed here, extends and further tests the premises and applications of this research by partnering faculty members who teach large, general education courses at IU.
Exploring relationships Between the New Indiana Academic English Test (IAET) and External Measures
Sun-Young Shin (Second Language Studies)
The proposed study will explore the relationships between students' standardized language test scores (e.g., the TOEFL iBT and IELTS) and the IAET writing and listening scores to establish the concurrent validity and also examine the consequential validity of the test by comparing the students' GPA data across groups of students who are exempted, tested out, placed into different ELIP courses, or do not comply with placement recommendations based on test scores.
Evaluating the Effect of Course-specific Library Instruction on Student Success
Andrew Asher (Anthropology and IU Libraries)
Using records of course-specific instruction provided by the IUB Libraries, this study will evaluate the impact of library instruction sessions on measures of students academic success and educational development.
S&H Fulfillment Patterns and Their Effect on Student Retention
Kalani Craig (History)
To encourage balance between degree completion and graduating with appropriate skills, the goal is to study patterns in student fulfillment of IUB GenEd S&H (Social & Historical Studies) requirements and attempt to understand how the variety of options available for S&H transfer credits affects student engagement, retention, and performance.
Inflection Points of Economics Majors: A closer look at enrollments in Intermediate Microeconomics (E321)
Paul Graf (Economics)
In this follow-up study, the plan is to address potential correlation between instructor selection, class pedagogy, and student preferences and expectations in Intermediate Microeconomics (E321) and when and possibly why students opted in or out of an Economics major.
The Impact of the Becoming the Best Student
Anthony Guest-Scott (Student Academic Center)
This study will analyze the impact of two of IUB classes about college classes, college academics, and college life more generally. These metaclasses support a broad range of students, including first-generation, transfer, international, students on probation, and students who are motivated to improve their college learning.
Using Analytics to Compare Student Demographics For Different Delivery Methods (Face to Face, Hybrid, Online) of AMST-A 100 What is America?
Vivian Nun Halloran (English and American Studies)
The American Studies department is reconfiguring one of its introductory courses (AMST-A 100 What is America?) and this study will use student analytics data to analyze student success in current courses compared to past years' courses, focusing on various methods of delivery (face to face, hybrid, and online) and enrollment size.
Analyzing the Transition from Developmental to Supplemental Education
Daniel Hickey (Education Counseling & Educational Psychology)
The proposed project will explore all manner of accessible IUB evidence regarding undergraduate developmental and supplemental instruction. The project will then search for ways to use this data to study and enhance the precision with which students are placed in or offered these services and the success of these services.
Determinants of Students Choices of Undergraduate Majors and the Program Strategies
Michael Kaganovich (Economics)
The project focuses on (i) quantifying the factors that contribute to IU students' choices of majors, (ii) inferring the actions and policies of major programs in effecting those student decisions, (iii) the statistical relationship between mid-career salaries associated with IU majors and curricular requirements and grading standards in them, and (iv) the patterns of students' "switching" between the programs.
Role of Peer Networks in Student Choice of Academic Major at IUB
Adam Maltese (Education Curriculum & Instruction)
This study will focus on trying to evaluate the role of peer networks on major choice and persistence from two angles: 1) analysis of existing institutional data on course enrollments to discover networks based on co-enrollment; and 2) analysis of data from an ongoing study on major choice to understand how peer networks develop and evolve, and what roles these networks may play in major choice and persistence.
The HumAn Learning Project Phase II
Jennifer Robinson (Anthropology)
Phase II of the HumAn Learning Project (1) refines our understanding of these trends with multivariate modeling and by comparing them to student success in other IU general education courses, (2) assesses variability of student success across sections of course, (3) analyzes student performance over time, and (4) begins to implement interventions based on Phase I findings.
Ethical Innovations: Exploring How Moral Reflection Benefits Learning Analytics Development
James Willis III, Joshua Quick (Education Counseling & Educational Psychology)
Using student data for the purposes of learning analytics incurs various ethical problems in the processes of curation, analysis, implementation, and modeling. This study will develop ethical approaches to using student data that is both timely and applicable for users of learning analytics.
MOOC Visual Analytics Tools
Katy Borner (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.
Transforming Education, Stimulating Teaching and Learning Excellence
The Transforming Education, Stimulating Teaching and Learning Excellence (TRESTLE) project is a multi-institutional intellectual community focused on increasing the number of students graduating within STEM disciplines. At IU Bloomington, computer science faculty are using a learner-centered approach to their teaching, in pursuit of better learning outcomes and student success, as they collaborate with faculty from other STEM programs from the US and Canada.