We are hiring: Kaneb Center Postdoctoral and Graduate Associates in Learning Research

Kaneb Center Postdoctoral and Graduate Associates in Learning Research

Description:

The ND Learning | Kaneb Center for Teaching Excellence seeks graduate students and postdocs to serve as Kaneb Center Postdoctoral and Graduate Associates (PGAs) in the Research and Assessment for Learning (ReAL) Lab for the 2020-2021 academic year. The PGA will become acquainted with the fundamental concepts and core practices of the Scholarship of Teaching and Learning (SoTL), an inquiry that examines the intersection of instruction and student learning across disciplines in higher education. 

A potential PGA would work with a team of faculty on course assessment, program/grant evaluation, conference proposals/presentations, and support articles for publication.  If hired you would participate in applied learning research and work toward submitting at least one co-authored article for publication, submitting a conference and/or grant proposal, and creating a culminating poster presentation or conducting faculty SoTL and assessment-related workshops. This position is an excellent opportunity to develop as a professional,  a teaching scholar-practitioner. For more information see the ReAL Lab blog at: https://kaneb.nd.edu/real/.

Details:

Throughout the academic year, PGAs contribute an average of 5 hours per week, scheduled

according to availability, and receive pay of $20/hour. They attend weekly meetings with Dr. G. Alex Ambrose, Director of Learning Research at Notre Dame Learning | Kaneb Center. 

Applicants should have completed one or more semesters of TAing or teaching, preferably at Notre Dame, before holding this position. Postdocs may be eligible; contact gambrose@nd.edu for more information. Advisor and DGS approval will be required before hiring is finalized. Applicants must be in residence during the fall 2020 and spring 2021 semesters. 

To apply, please submit the information below to kaneb@nd.edu by 11:59pm, Wednesday April 27, 2020. Interviews will take place in late April and early May.

– Name

– Phone

– Email

– Department

– Current year in graduate school & anticipated year of graduation

– Paragraph describing your interest in this position

ND Trains 170 Paraguayan Legal Professors in Online Teaching Pedagogies and Learning Technologies during COVID-19

The US State Department funded a USAID grant to have the University of Notre Dame and Harvard join the Paraguayan Development Institute’s led program named “Rule of Law and Culture of Integrity” (ROLCI) in Paraguay. The ROLCI Program is an initiative of Development Institute (ID)and the United States Agency for International Development (USAID). The goal was to strengthen Paraguayan higher education institutions to improve the rule of law and culture of anti-corruption in Paraguay. The team, lead by the Keough School of Global Affairs’s Pulte Institute for Global Development, gathered trainers and experts from ND Learning | Kaneb Center, OIT”s Teaching and Learning Technologies Group to create, translate, facilitate, and record an interactive webinar series on using state of the art technologies and online pedagogies during and after COVID-19. 170  legal professors from several law schools and training centers in Paraguay such as the National University of Asunción, the National University of Ciudad del Este, the National University of Concepcion and the National University of Caaguazu, the International Center for Judicial Studies of the Supreme Court of Justice, the Public Defense Ministry’ training center, the Judicial School of the Council of the Magistracy and the Public Ministry Training Center, attended and participated in the 6-part live dual-language series. Individual workshops included the following topics and goals (note: the links are to the shared zoom recordings and translated slide decks):

Workshop TitleDescription & Goals Links to Recordings
Online Learning Exploratory Session•Country and Campus exchange
•Open dialogue and needs assessment 
Recording
Flexible Teaching & Learning Course Design•Reassess your course design: situational factors, learning goals, and assessment structure for resilient teaching
•Develop broad strategies for engaging your students and helping them achieve the course learning goals regardless of class modality
•Describe general principles of resilient teaching 
•Apply principles of inclusive teaching that apply across modalities
Recording

Flexible Teaching Methods Part 1: Live and Pre-Recorded Lecturing with Zoom•Utilize basic pedagogical design principles for using Zoom technology for synchronous and asynchronous teaching
•Experience as a participant in a live Zoom session with backchannel chat, share/annotate screen, live polling and documents
Recording
Flexible Assessment Part 1 (Summative): Alternative Assessments & Exam (Re)Design•Describe different exam methods and forms
•Redesign (if needed) your traditional exam/assessment for a remote classAdapt administration procedures to the online environment
Recording
Flexible Teaching Methods Part 2: Active Learning Strategies with Free Google Tools•Understand the reasons for incorporating active learning
•Describe & experience possible tools and strategies for hybrid active learning
•Select & apply active learning strategies
Recording
Flexible Assessment Part 2 (Formative): Assessing Participation, Preparation, and Attendance•Understand the difference and relationship between formative and summative assessment
•Define the role and value of participation, preparation, and attendance in a resilient class
•Apply concrete strategies for using participation, preparation and attendance for formative assessment purposes
Recording

Key collaborators on this project included:

  • Edward Jurkovic, Program Manager. Pulte Institute for Global Development
  • Lorena Gaona Greenwood, Monitoring and Evaluation Specialist, Development Institute
  • G. Alex Ambrose Phd, Director of Learning Research, Kaneb Center, Notre Dame Learning
  • Jennifer Zachman, Associate Professor, Modern Languages, Saint Mary’s College
  • Kevin Abbott, Educational Technology Specialist, OIT
  • Kristi Rudenga PhD, Director of Teaching Excellence, Kaneb Center, Notre Dame Learning
  • John Kuehn, Adjunct Professor of Law, Notre Dame Law School 
  • Kari Gallagher, Adjunct Professor of Law, Notre Dame Law School
  • John Conway, Adjunct Professor of Law, Notre Dame Law School

For more information about this project see:

Inclusive learning analytics for identifying and boosting non-thriving students in large-enrollment general chemistry course

Schalk, Catlin, Young, Kelley, Ambrose, G. Alex, Duan, Xiaojing, Weber, Woodard, Victoria (2020) “Inclusive learning analytics for identifying and boosting non-thriving students in large-enrollment general chemistry course.” Biennial Conference on Chemical Education. Poster.

Because of the global COVID-19 pandemic, the 2020 Biennial Conference on Chemical Education was terminated on April 2, 2020, by the Executive Committee of the Division of Chemical Education, American Chemical Society; and, therefore, this presentation could not be given as intended

ABSTRACT
Our goals are to identify non-thriving students in a gateway introductory chemistry course, and to develop methods that increase student success and retention rates in the College of Science and College of Engineering. General Chemistry is required for all first semester STEM majors, which totaled 949 students in Fall 2019. Specifically, our focus is on maximizing students’ potential to thrive — that is earning a final grade of C or higher in the course — not just to survive the class. We use student background data, historical performance data, as well as real-time academic performance data in the development of a visual analytics dashboard. This inclusive learning platform is a tool for instructors and administration to identify admissions characteristics and academic performance triggers that lead to non-thriving in the course, or in STEM programs. Course homework and exam item analysis was conducted to identify students who are not likely to thrive based on course performance identifiers so that early actions can be taken to intervene during the semester to boost the chances of these students to thrive in the course. Additionally, a special treatment program, the Science and Engineering (S&E) scholars program, is implemented as an effort to close the achievement gap of underserved and underprepared students while also maintaining the rigor of the course. The 45 students in this small cohort take a summer math refresher course, are enrolled in the same chemistry and calculus sections together, have a reduced course load, and attend extra graded problem solving classes with more one-on-one time with experienced professors and TAs.

ASEE Paper & Presentation: Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course

One Sentence Overview:
•This study identified students that had the potential to be “non-thriving” at the end of the semester based on historical data and boosted these students in an attempt to improve their performance in the course.

Key Takeaways:
• A trigger of 80% or lower on one of the first three homework assignments was successfully implemented to identify and boost potentially “non-thriving students”.
• Students who responded to the personalized action plan in their boost email performed better than those who did not respond and those who would have been boosted based on the same trigger in the 2017 and 2018 fall semesters.

Citation & Link to the Full Paper & Slides:
Bartolini, A.; Running, C.; Duan, X.; Ambrose, G. Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course. 2020 ASEE Virtual Annual Conference Content Access Proceedings. 2020.

Click here for the presentation slides

5 Min Screencast Video Demo of the PerformanceVis Dashboard

Duan, Xiaojing, Ambrose, G. Alex, Wang, Chaoli, Abbott, Kevin, Woodard, Victoria, Schalk, Catlin (2020) PerformanceVis: Homework & Exam Analytics Dashboard for Inclusive Student Success. Learning Analytics & Knowledge Conference. Practitioner Demo. Frankfurt, Germany

PerformanceVis is a visual analytics tool developed for analyzing and visualizing students’ chemistry course performance through the lens of time, homework and exams, and demographic and academic background. The Introduction to Chemical Principles course is a required course for all college of science and college of engineering programs at the university and is the second largest course on campus with approximately 1,000 freshmen taking the course.

This engaging tool includes four main views (overall exam grade pathway, detailed exam grade pathway, detailed exam item analysis, and overall exam & homework analysis) which are dynamically linked together for user interaction and exploration. PerformanceVis enables instructors to improve their course and assessment design by visualizing students’ perceived difficulty level and topic correlation between assignments and exams. It assists instructors and administrators in evaluating the impact of a special treatment program (cohort) by reviewing the performance of regular, control, and cohort students overall and by exam. The image below shows a screenshot of PerformanceVis with the right side of the image showing a view of the gender performance gap for those students who were not thriving. The left side of the image shows Exam 1 item analysis for each test question.

Link to 5 min practitioner interactive demo on YouTube

Link to the Interactive Dashboard Tool:

Workshop: Improve your Teaching & Student Learning with Research from the Classroom

Ambrose, G. Alex, Hubert, Dan, Rouamba, Guieswende (2019) “Improve your Teaching Student Learning with Classroom Research.” Kaneb Center for Teaching Excellence Workshop, Notre Dame, IN.

Click here for the slide deck
Click here for the handout

Participants will:

  • Explore the landscape of Discipline-Based Research (DBR) and the Scholarship of Teaching and Learning (SoTL).
  • Brainstorm potential research goals, questions, and data for their own course.
    Become familiar with applied learning research support services and resources (e.g. survey/rubric design, video observation, consent forms, and umbrella IRB).

 

Practitioner Report: Learning Analytics for Inclusive STEM Student Success

Duan, Xiaojing, Ambrose, G. Alex, Wang, Chaoli, Abbott, Kevin, Woodard, Victoria, Young, Kelley (2020) Learning Analytics for Inclusive STEM Student Success. Learning Analytics & Knowledge Conference. Practitioner Report and Poster. Frankfurt, Germany

ABSTRACT: The challenge was to identify and help underserved and underprepared students in an introductory chemistry course to be retained and thrive in the college of science or engineering while supporting the general population. In this paper, we describe our methods for identifying these students, evaluating the impact of a special treatment program that was provided to a subset of those students, discuss our efforts to help the general population, and evaluate the short- and long-term impacts. In particular, we discuss a data-informed framework for analyzing student and outcome variables.

Keywords: STEM Retention; Learning Visualization Dashboard; Inclusive Pedagogy; Learning Analytics

Click here for a current version of the practitioner report

Closing the Learning Analytics Loop with Advising & Interventions – Interactive Infographic Poster Prezi, Recorded Presentation & Full Paper:

Click here to download and zoom into the infographic poster presentation as a pdf

Click here to watch on Youtube the 19 min full recorded presentation
at the Learning Analytics Conference

Click here to access the interactive infographic visual tour via Prezi
(click on the “present” button below)

For the full research paper see:

Syed, M., Anggara, T., Duan, X., Lanski, A., Chawla, N. & Ambrose, G. A. (2018) Learning Analytics Modular Kit: A Closed Loop Success Story in Boosting Students Proceedings of the International Conference on Learning Analytics & Knowledge

Abstract

Identifying non-thriving students and intervening to boost them are two processes that recent literature suggests should be more tightly integrated. We perform this integration over six semesters in a First Year Experience (FYE) course with the aim of boosting student success, by using an integrated closed-loop learning analytics scheme that consists of multiple steps broken into three main phases, as follows: Architecting for Collection (steps: design, build, capture), Analyzing for Action (steps: identify, notify, boost), and Assessing for Improvement (steps: evaluate, report). We close the loop by allowing later steps to inform earlier ones in real-time during a semester and iteratively year to year, thereby improving the course from data-driven insights. This process depends on the purposeful design of an integrated learning environment that facilitates data collection, storage, and analysis. Methods for evaluating the effectiveness of our analytics-based student interventions show that our criterion for identifying non-thriving students was satisfactory and that non-thriving students demonstrated more substantial changes from mid-term to final course grades than already-thriving students. Lastly, we make a case for using early performance in the FYE as an indicator of overall performance and retention of first-year students.

Related:

Video Story & Award Presentation Slides: Kaneb, OIT, and FYS Team win 2018 Apereo Teaching And Learning Award (ATLAS)

Paper Published: Learning Analytics Modular Kit: A Closed Loop Success Story in Boosting Students

Our paper got accepted with a 32% acceptance rate this year!

Syed, M., Anggara, T., Duan, X., Lanski, A., Chawla, N. & Ambrose, G. A. (2018) Learning Analytics Modular Kit: A Closed Loop Success Story in Boosting Students Proceedings of the International Conference on Learning Analytics & Knowledge.

ABSTRACT
Identifying non-thriving students and intervening to boost them are two processes that recent literature suggests should be more tightly integrated. We perform this integration over six semesters in a First Year Experience (FYE) course with the aim of boosting student success, by using an integrated closed-loop learning analytics scheme that consists of multiple steps broken into three main phases, as follows: Architecting for Collection (steps: design, build, capture), Analyzing for Action (steps: identify, notify, boost), and Assessing for Improvement (steps: evaluate, report). We close the loop by allowing later steps to inform earlier ones in real-time during a semester and iteratively year to year, thereby improving the course from data-driven insights. This process depends on the purposeful design of an integrated learning environment that facilitates data collection, storage, and analysis. Methods for evaluating the effectiveness of our analytics-based student interventions show that our criterion for identifying non-thriving students was satisfactory and that non-thriving students demonstrated more substantial changes from mid-term to final course grades than already-thriving students. Lastly, we make a case for using early performance in the FYE as an indicator of overall performance and retention of first-year students.