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LASER Institute

The Learning Analytics in STEM Education Research (LASER) Institute is a professional development program for early and mid-career researchers and funded by the National Science Foundation (ECR: BCSER).

As the use of digital teaching and learning resources continues to expand, the volume and variety of data available to researchers presents new opportunities for understanding and improving STEM education. The LASER Institute aims to increase the capacity of early and mid-career scholars to leverage new data sources and apply computational methods (e.g., network analysis, text mining and machine learning) to support their existing research and develop new lines of inquiry. Located at the Friday Institute for Educational Innovation, the LASER Institute is a collaborative effort between North Carolina State University, University of Florida and the University of Tennessee, Knoxville.


  • Disciplinary Knowledge: Scholars will deepen their understanding of LA methodologies, literature, applications and ethical issues as they relate to STEM education and equity.
  • Technical Skills: Scholars will develop proficiency with R, RStudio, GitHub and other tools used for collaboration, reproducible research and computational analysis.
  • Social Capital: Scholars will expand their professional networks, connecting with researchers and experts in LA related fields, as well as other scholars focused on STEM education.


Applicants for the 2023 institute must have completed the requirements for a Ph.D. or Ed.D. degree by December 2020. Early-career scholars are typically under seven years after obtaining a doctoral degree; mid-career scholars are typically within their first 15 years of academic or other research-related employment. In support of the broader goals of the Building Capacity in STEM Education Research (BCSER) program, the LASER Institute will prioritize early and mid-career scholars from underrepresented groups and faculty at minority-serving institutions. Prospective LASER Scholars will have a primary job responsibility or specific aspect of their research agenda that would benefit from participation in the LASER program. As part of the application process, prospective participants will need to articulate this connection.


The LASER Institute will kick off with a week-long summer workshop that will run from July 17-21 and be hosted in Raleigh, NC, on the campus of North Carolina State University. A reimbursement allowance for $1500 will be provided for travel, lodging, and evening meals (breakfast and lunch will be provided each day) to support participation.

Participants who will benefit most from the LASER Institute are scholars who:

  • Are currently engaged in research in STEM education contexts;
  • Are relatively new to data sources and techniques used in Learning Analytics research;
  • Have a STEM Ed research question or topic in mind;
  • Have either primary job duties or a research agenda that directly incorporate Learning Analytics research;
  • Need guidance on how new data sources and techniques can support their research;
  • Have access to a dataset or study population of interest;
  • Have a basic understanding of probability and statistical analysis;
  • Have experience using statistical software programs for data cleaning and analysis (e.g. SPSS, Stata, SAS, R);
  • Have the time necessary to devote to developing their skills and supporting a research effort in the upcoming year (e.g. manuscript submission, grant submission, conference presentation).

Participants in the LASER Institute are expected to commit to the following:

  • Attend the in-person Summer Institute from July 17-21 (virtual options are not available);
  • Attend the virtual monthly check-ins that will be the third Thursday of each month from August – December; and
  • Complete a project that is either related to your primary work responsibilities and/or research agenda.

LASER Institute Interest Form


Institute Details

The LASER Institute is a year-long program consisting of two core components:

  1. Summer Workshop: The Friday Institute will host an intensive 5-day program consisting of learning labs, research planning sessions, and guest speakers.
  2. Online Community: An online community of practice for ongoing networking and support throughout the year.

The weeklong intensive program will be conducted at North Carolina State University in Raleigh, North Carolina

Program activities are designed to prepare researchers with the knowledge, skills and resources necessary for more advanced study of LA and for collaborating with researchers and practitioners from different backgrounds, especially those from advanced data analytics. By the end of the program, participants will be able to:

  • Describe STEM education questions/issues addressed by LA and associated analytical approaches/applications;
  • Identify relevant and appropriate STEM educational data sources for computational analyses;
  • Apply computational techniques (e.g. machine learning and text mining) using R and RStudio to prepare, explore and model STEM education data;
  • Evaluate both the technical feasibility and ethical issues in using analytics to support STEM teaching and learning, and school and district-level decision-making; and
  • Develop a collaborative research agenda in STEM education that seeks to address challenges in STEM education from a Learning Analytics lens.

Learning Labs during the summer program are designed to provide participants hands-on experience with R to apply learning techniques, including text mining, data visualization, social network analysis and machine learning. Students will gain hands-on experience in analyzing educational data from STEM contexts, preparing them to solve practical problems in cutting-edge STEM education research and practice. Data for learning labs will come from Friday Institute Online Professional Learning courses (in particular Technology and Math Educators), social media posts, ASSISTments math practice tool, the CODAP data exploration tool, and other digital teaching and learning platforms used in STEM education. Curriculum for the LASER Learning Labs will address the following areas:

  1. Introduction to Learning Analytics is designed to provide participants an overview of the field of Learning Analytics and prepare students for using tidy data principles and producing replicable research using R, RStudio and GitHub.
  2. Visualizing STEM Learning will focus on the use of R packages such as ggplot2 and shiny for plotting learner data, creating attractive and informative charts, and developing interactive web apps and dashboards.
  3. Machine Learning in STEM Ed will introduce researchers to applications of Machine Learning in STEM educational settings and prepare them to conceptualize educational problems, build and evaluate models, and work with a wide range of algorithms and methods to address those problems.
  4. Text Mining in Education will provide an introduction to text mining concepts, applications in STEM Ed contexts, and applied experience with widely adopted tools and techniques such as tf-idf and sentiment analysis, topic modeling and classification.
  5. Analyzing Learning Networks will introduce students to social network theory and how network analysis can be applied in online and blended learning environments. Students will learn to calculate network statistics, visualize network properties and use modeling to discover underlying structures and factors impacting their development.

In support of the NSF’s broad goal of building individuals’ capacity to conduct high-quality STEM education research, participants will receive daily support during the Summer Session in developing a research topic that could be investigated further. To maximize time, presentations and panels will be combined with a working lunch. To help provide a personalized learning experience, participants will be initially put into one of the two following groups based on their responses to the needs assessment administered prior to the Institute:

  1. Technical Assistance will be aimed at participants who have a solid research idea but need support with specific techniques or packages in R. Technical assistance needs may have commonalities between participants or may be participant specific. To determine the most effective response to participant needs, the participants will respond to an online poll each day that allows for up/down voting. In real-time, participants will see technical issues that others are having and may vote issues up/down. This will allow for subgrouping of participants and also identify common problems that can be addressed.
  2. Research Planning is for participants that need help developing a research idea. For this group, we will make use of low stakes writing activities (Bean, 2011) followed by peer sharing. Our goal is for these participants to have a research idea and plan of action by the end of the week.

During the Summer Workshop, broader topics related to disciplinary knowledge will be addressed at the end of each day through presentations, guest speakers and panel discussions. Speakers will consist of institute instructors, invited guests, advisory board members and past participants with topics including, but are not limited to:

  • Digital Data in Education will introduce participants to three types of digital data that frame the analytical approaches addressed by this Institute, as well as three types of educational technologies in which these data are captured and stored. Specifically, this presentation will cover structured data, unstructured text data, and network data obtained from digital learning environments, administrative data systems, and sensors and recording devices.
  • Frameworks and Workflows will introduce participants to general approaches to conceptualizing processes associated with LA, including data collection, storage, cleaning, exploring, and modeling. These frameworks and workflows will help illustrate LA’s emphasis on actionable insight to better target instructional, curricular and support resources and interventions.
  • Researcher-Practitioner Partnerships will highlight the value of interdisciplinary collaborations with educational organizations to help them learn from their own data and identify new ways to support students. This presentation will include examples from the field and discuss the conditions necessary for developing and sustaining these partnerships.
  • Legal and Ethical Issues will address considerations for researchers that are unique to working with data in these new types of STEM learning environments. Topics will include issues such as explicit and implicit bias embedded in big data and algorithms, adequately protecting data, and appropriately addressing privacy concerns.

A core component of the LASER Institute will be an online community of practice to provide follow-up support to the Summer Workshop and continued professional learning, mentoring, and networking opportunities throughout the year. The LASER online community will include monthly activities and regularly updated resources.

  • Facilitated discussions will be hosted on our learning and social media platforms. Facilitated discussions will focus on shared problems of practice such as reproducible research along with community forums for topic areas such as R-related Help, general announcements, specific methods.
  • Zoom Webinars will be led by instructors, guest speakers and past participants designed to extend topics introduced at the Summer , address critical issues raised in the community, and provide deeper dives into learning analytics methods.
  • Peer review activities will be coordinated by the project team so participants can receive timely formative feedback on research products (e.g., code, analyses, presentations, manuscripts or proposals) before a more formal review by the broader academic community.
  • A resource repository consisting of both instructor and member-generated content will be hosted in our Professional Learning and Collaborative Environment (PLACE) platform and accessible through modern tools such as GitHub to model and support participant engagement with modeling best practices in learning analytics research.
  • Dr. Tiffany Barnes is a Professor of Computer Science at NC State University. Dr. Barnes has served as chair and board member of the International Educational Data Mining Society and received an NSF CAREER Award for her novel work using educational data mining to add intelligence to STEM learning environments. Dr. Barnes is co-Director for the STARS Computing Corps, a consortium of universities that engage college students in outreach, research, and service to broaden participation in computing.
  • Dr. Gregory Downing is an Assistant Professor in STEM Education at North Carolina Central University, an HBCU. Dr. Downing’s research explores equity and diversity issues within STEM education, specifically how current teaching and learning practices within the K-16 system (dis/en)able students of color and other marginalized students to/from entering STEM careers.
  • William Finzer has been developing educational software for over 30 years. He is a skilled software designer and programmer with considerable experience in classroom teaching, teacher professional development, game design, curriculum development, and research. As Senior Scientist and project lead for the Common Online Data Analysis Platform (CODAP) project at Concord Consortium, he leads design and development of a free, open source, browser-based data analysis and exploration environment adaptable to a wide variety of educational settings.
  • Nancy Rausch is a senior manager and data scientist at SAS. Nancy has been involved for many years in the design and development of SAS’s data warehouse and data management products, working closely with customers and authoring a number of papers on SAS data management products and best practice design principles for data management solutions.
  • Dr. Alyssa Wise is an Associate Professor of Learning Sciences and Educational Technology in the Steinhardt School of Culture, Education, and Human Development and the Director of LEARN, NYU’s university-wide Learning Analytics Research Network. Dr. Wise directs LEARN with the aim of making NYU a leader in data-informed teaching and learning while also generating new knowledge about how LA can promote equitable and effective education.

2023 Cohort

Megan AthaAssistant ProfessorFlorida Gulf Coast University
Yu BaoAssistant ProfessorJames Madison University
Le Shornn BenjaminAmerican Society of Engineering Education Post Doctoral ResearcherUniversity of Houston/American Society of Engineering Education
Rogers BhalalusesaLecturerThe Open University of Tanzania
Emily BonemAssistant Director, Scholarship of Teaching & LearningPurdue University
Daniela Castellanos ReyesIncoming Assistant ProfessorNorth Carolina State University
Xiaowen ChenAssistant ProfessorWestern Kentucky University
Deborah CockerhamClinical Assistant ProfessorUniversity of North Texas
Liliana Donchik BelkinSenior Lecturer in EducationUniversity of Roehampton
Suzhen DuanAssistant ProfessorTowson University
AJ EdsonResearch Assistant Professor of Mathematics EducationMichigan State University
Fei GaoProfessorBowling Green State University
Taren GoingPostdoctoral Research AssociateMichigan State University
Angela HemingwayEducation AdvisorT-Mobile
Jianlin HouSpecialistThe School District of Palm Beach County
Itauma ItaumaDivision Chair & Assistant ProfessorNorthwood University
Hyeon-Ah KangAssistant ProfessorUniversity of Texas at Austin
Victor LawAssociate Professor and Program DirectorUniversity Of New Mexico
Jin LeeAssistant ProfessorUniversity of Louisiana at Lafayette
Seung LeeAssistant Professor of EducationPepperdine University
Alfredo LeonAssistant ProfessorMiami Dade College
Cynthia LimaAssistant Professor of STEM EducationUniversity of Texas at San Antonio
Jin LiuClinical Associate ProfessorUniversity of South Carolina
Peng LuAssistant ProfessorUniversity of Georgia
Catherine ManlyPostdoctoral ResearcherCity University of New York
Praveen MeduriAssistant ProfessorCalifornia State University
Nadia MillsAssociate Professor of MathematicsUniversity of the Virgin Islands
Matthew MorenoPostdoctoral ResearcherMcGill University
Ceren OcakAssistant Professor of Instructional TechnologyGeorgia Southern University
Erin OttmarAssociate Professor of Learning SciencesWorcester Polytechnic Institute
Eunsung ParkAssistant ProfessorTennessee Tech University
Fabio Andres Parra MartinezPostdoctoral Research FellowUniversity of Arkansas
Yingxiao QianClinical Assistant ProfessorUniversity of South Carolina
Tacey RodgersDirector, Assessment, Research, and EvaluationSolano County Office of Education
Arthur SikoraAssistant Professor of ChemistryNova Southeastern University
Vipin VermaAssistant Research ScientistArizona State University
Ning WangResearch AssociateThe University of Texas at Dallas
Korah WileyLearning ScientistDigital Promise
Mia WilliamsAssistant ProfessorUniversity of Wyoming
Fan XuSenior Learning DesignerThe Ohio State University
Zhen XuPostdoc Research AssociateUniversity of North Carolina at Chapel Hill
Clement G. YedjouAssociate Professor of BiologyFlorida A & M University
Ji Hyun YuAssistant ProfessorUniversity of North Texas
Dake ZhangAssociate ProfessorRutgers, the State University of New Jersey
Enyu ZhouSenior Research AnalystCouncil of Graduate Schools

2022 Cohort

NameJob TitleInstitution
Brittany AndersonAssistant Professor, Urban EducationUniversity of North Carolina at Charlotte
Alexandria ArdissoneAssistant ScientistUniversity of Florida
Tracy ArnerPostdoctoral Research ScholarArizona State University
Catherine BlatAssistant Dean for Student ExperiencesEngineering/UNC Charlotte
Irina CainAssociate LecturerUniversity of Massachusetts Boston
Deborah CockerhamClinical Assistant ProfessorUniversity of North Texas
Michael DaleyAssociate Professor of EducationUniversity of Rochester
Kristi DonaldsonPartner Relations ManagerThe Learning Partnership
Krista DulanyResearch Assistant ScientistUniversity of Florida
Mona EmaraResearch Fellow, Lecturer of Edu. PsychologyUniversity of Vienna, Austria. Damanhour University, Egypt
Lori FootePostdoctoral ResearcherUniversity of Cincinnati
Liz FrechetteSenior Research and Policy AssociateUniversity of Oklahoma
Peng HePostdoctoral Research AssociateMichigan State University
Susan HibbardSenior Director of Learning Science and PsychometricsBlueprint Test Preparation
Ahmed IbrahimSenior Education Research ConsultantJohns Hopkins University
Justina Rodriguez JacksonResearch ScientistGeorgia Institute of Technology
Jillian LauerPostdoctoral FellowNew York University
Mark LaVeniaData StrategistEdReports
Sungwoong LeeAssistant ProfessorUniversity of West Georgia
Kathryn LeechAssistant ProfessorUniversity of North Carolina at Chapel Hill
Alex LishinskiResearcherUniversity of Tennessee-Knoxville
Kathryn McCarthyAssistant ProfessorGeorgia State University
Veronica MinayaSenior Research AssociateTeachers College at Columbia University
Nadun Kulasekera MudiyanselageAssistant ProfessorAppalachian State University
Jennifer OsterhageAssistant Professor of BiologyUniversity of Kentucky
Tom PennistonCoordinator of Learning Analytics
University of Maryland, Baltimore County
Shalaunda ReevesAssistant Professor in STEM EducationUniversity of Tennessee
Lisa RidgleyResearch AssociateJacobs Institute for Innovation in Education/University of San Diego
Margarita SafronovaAssociate Director, Academic CoordinatorUniversity of California, Santa Barbara
Guan SawAssociate ProfessorClaremont Graduate University
Celia ScottAssistant Dean of Assessment and Associate ProfessorUniversity of North Texas Health Science Center
Jung Mi ScoulasAssistant ProfessorUniversity of Illinois Chicago
Jenay SermonSenior Director Applied Learning Science / Education PT FacultyKenzie Academy from Southern New Hampshire University / Florida A&M University
Damji StrattonE-Learning Research & Data Analyst SpecialistMissouri Online, University of Missouri System
Robert TalbertProfessor of Mathematics and Presidential Fellow for the Advancement of LearningGrand Valley State University
Ashley VaughnAssociate Director/Assistant Professor of PracticeNorthern Kentucky University
Emily WeigelSenior Academic ProfessionalGeorgia Institute of Technology
Melinda WhitfordResearch AnalystUniversity at Buffalo
Rachel WongAssistant Professor of Educational PsychologyTexas A&M University-Commerce
Kim WrightAssistant Research ScientistTexas A&M University
Cristina ZepedaPostdoctoral Research AssociateWashington University in St. Louis
Ya Zhang
Assistant Professor

Western Michigan University
Meina Zhu
Assistant Professor
Wayne State University

2021 Cohort

Mete AkcaogluAssociate ProfessorGeorgia Southern University
Zina AlaswadAssistant Professor of Interior DesignTexas State University, School of Family and Consumer Sciences
Tawannah G. AllenAssociate Professor of Educational LeadershipStout School of Education, High Point University
Rebecca Y. BayeckCLIR Postdoctoral FellowSchomburg Center for Research in Black Culture
Laurie O. CampbellAssistant ProfessorUniversity of Central Florida
Jacqueline G. CavazosPostdoctoral ScholarUniversity of California, Irvine
Shonn Sheng-Lun ChengAssistant ProfessorSam Houston State University
MeganClaire CoglianoPostdoctoral FellowUniversity of Nevada Las Vegas
Yvonne EarnshawAssistant Professor and Program Coordinator of Instructional Design and DevelopmentUniversity of Alabama at Birmingham
Carlton J. FongAssistant ProfessorTexas State University
Hoda Harti
Instructor, Educational Technology
Northern Arizona Univesity
Yu-Ping HsuAssistant ProfessorWestern Illinois University
Diane IgocheAssistant ProfessorRobert Morris University
Carrie JonesScience TeacherWake County Schools
Yeo-eun KimPostdoctoral FellowWashington University in St. Louis
T.K. KuykendallAdjunct/Coordinator of DataCleveland State University/Lakewood City Schools
Yanju LiData Administrator Lead
Georgia State University
Lin LinProfessorUniversity of North Texas
Peggy LisenbeeAssociate Professor of Early Childhood Education
College of Professional Education, Texas Woman’s University
Nikki G. LobczowskiPostdoctoral AssociateUniversity of Pittsburgh
Chrishele MarshallProgram Associate I, Implementation and Training (Assessment)Detroit Public Schools Community District
Tara MasonAssisant Professor of Inclusive EducationWestern Colorado University
Becky Matz
Research Scientist, Center for Academic Innovation
University of Michigan
T.J. McKennaLecturerBoston University
Vida MingoSenior LecturerColumbia College (SC)
Angela MurilloAssistant ProfessorSchool of Informatics and Computing, Indiana University-Purdue University Indianapolis
Jeffrey T. OlimpoAssistant Professor in Biological SciencesThe University of Texas at El Paso
Patricia Ortega-ChasiAssistant ProfessorUniversidad del Azuay
Mihwa ParkAssistant ProfessorTexas Tech University
Kim Pinckney-LewisHR StrategistNational Security Agency
Tiffany RomanAssistant Professor of Instructional TechnologySchool of Instructional Technology and Innovation, Kennesaw State University
Teomara (Teya) RutherfordAssistant Professor, Learning SciencesUniversity of Delaware
Jaime SabelAssistant ProfessorUniversity of Memphis
Justice T. WalkerAssistant Professor of STEM EducationThe University of Texas at El Paso
Nadia Monrose MillsAssistant Professor of MathematicsUniversity of the Virgin Islands


National Science Foundation


University of Florida

University of Tennessee, Knoxville

Project Team

Dr Shaun Kellogg

Dr Shaun Kellogg

Dr Shiyan Jiang

Dr Shiyan Jiang

Dr Hollylynne S. Lee

Dr Hollylynne S. Lee

Dr Rob Moore

Dr Rob Moore

Jennifer K. Houchins

Jennifer K. Houchins

Dr Joshua Rosenberg

Dr Joshua Rosenberg

Jeanne McClure

Jeanne McClure