ϡȱ�� Center for Academic Innovation - Adaptive Learning

Adaptive Tools for High-enrollment Online Courses Summit

admin-annika — Fri, 26 Jun 2020 21:11:39 +0000

Faculty, instructional designers, and teaching and learning center staff are invited to Adaptive Tools for High-enrollment Online Courses: Improving the COVID-19 Learning Experience for Students and Faculty, hosted by the ϡȱ�� Kirwan Center for Academic Innovation and the Association of Public and Land-grant Universities (APLU). This day-long summit will introduce participants to the ins and outs of adaptive courseware. Sessions will include lessons learned from faculty users, vendor demos, “birds of a feather” break-outs by discipline and role, and a closing plenary focused on pedagogical uses of adaptive courseware.

Learn More and Register: /cai/adaptive-tools-high-enrollment-online-courses

Areas of Focus:

Adaptive Learning

Cross Post:

Story

ALT-Placement Project

admin-annika — Mon, 20 Jan 2020 05:00:00 +0000

ALT-Placement Project: Investigating Adaptive Learning Tools for Mathematics Remediation and Placement

Only 28 percent of students enrolled in developmental courses will complete their degrees (Attewell, Lavin, Domina, & Levey, 2006). For most, placement into developmental math courses is determined by their score on a one-time, high-stakes exam taken shortly after being admitted to college. Increasingly, researchers have questioned the validity of these exams and the developmental course “treatment” that is required based on the outcomes of those tests (Medhanie et al., 2012; Melguizo et al., 2014).

In Fall 2017, the Kirwan Center received a $150,000 Phase I planning grant from the Kresge Foundation to explore the efficacy and feasibility of replacing the high-stakes mathematics placement exam process with a process that, instead, empowers students to assess and develop their mathematics knowledge using adaptive learning tools made available to them prior to matriculation. We believe these adaptive learning tools can deliver just-in-time skills remediation while also providing more reliable diagnostics of students’ knowledge, facilitating more accurate math course placements that will increase student success and lower costs by reducing the number of required non-credit developmental courses.

The primary goal of this project was to see if adaptive learning tools hold promise to: 1) more effectively diagnose and remediate mathematics knowledge and skills and, if so, 2) identify the one or two most effective and feasible use cases for further study in a more rigorous Phase II evaluation.

Read Final Report

Areas of Focus:

Adaptive Learning

PDF:

ALTPlacement-FinalReport-ExecSumm-20Jan2020.pdf

Initiatives Type:

projects

Cross Post:

Story

Call for Participation: ALT-Placement Project

admin-annika — Wed, 15 Nov 2017 15:52:40 +0000

The Kirwan Center is seeking institutional partners from across ϡȱ�� to participate in a Kresge Foundation funded project starting in Spring 2018 that will pilot the efficacy and feasibility of replacing the high-stakes mathematics placement exam process currently in use with a process that empowers students to assess and remediate their mathematics knowledge using adaptive learning tools instead. Our hypothesis is that these adaptive tools will deliver just-in-time skills remediation while also providing better diagnostics that will be a more reliable measure of students’ knowledge, thus enabling more accurate mathematics course placements that will increase persistence and lower costs.

If your institution is interested in participating in the 2018-19 pilot, please submit to cai@usmd.edu by Wednesday, November 22nd at 5:00 pm a 2-3-page overview outlining the intended use case that your institution would like to pilot.

Your overview should include:

A description of your current mathematics placement process and cut scores.
Which adaptive learning tool you intend to pilot (NROC EdReady or ALEKS)?
Which use case you intend to pilot?
The projected number of students you plan to engage in the project.
Plans for outreach and engagement to ensure student participation.
A timeline for implementation of the selected use case at your institution.
Project team names, role on project, and contact information (please indicate a project lead, at least one mathematics faculty member, and a research/data liaison to work with UMUC CILSS study team).
Any additional information that will help us to understand your institutional context.

Click here to download a PDF with more information.

News Type:

ϡȱ�� News

Areas of Focus:

Adaptive Learning

Cross Post:

News

Call for Participation: ALT-Placement Project

admin-annika — Wed, 15 Nov 2017 15:48:25 +0000

Your overview should include:

A description of your current mathematics placement process and cut scores.
Which adaptive learning tool you intend to pilot (NROC EdReady or ALEKS)?
Which use case you intend to pilot?
The projected number of students you plan to engage in the project.
Plans for outreach and engagement to ensure student participation.
A timeline for implementation of the selected use case at your institution.
Project team names, role on project, and contact information (please indicate a project lead, at least one mathematics faculty member, and a research/data liaison to work with UMUC CILSS study team).
Any additional information that will help us to understand your institutional context.

Click here to download a PDF with more information.

Areas of Focus:

Adaptive Learning

PDF:

ALT-PlacementProjectCFP-FINAL.pdf

Cross Post:

Story

Adaptive Learning

admin-annika — Wed, 15 Nov 2017 15:38:09 +0000

Adaptive learning is an educational method which uses computers as interactive teaching devices to orchestrate the allocation of human and mediated resources according to the unique needs of each learner. Computers adapt the presentation of educational material according to students' learning needs, as indicated by their responses to questions, tasks and experiences. The technology encompasses aspects derived from various fields of study including computer science, education, psychology, and brain science.

Most recently, the Kirwan Center sponsored a 1-day virtual conference to explore adaptive tools, entitled, Adaptive Tools for High-enrollment Online Courses: Improving the COVID-19 Learning Experience for Students and Faculty. This convening introduced participants to the ins and outs of adaptive courseware. Sessions included lessons learned from faculty users, vendor demos, “birds of a feather” break-outs by discipline and role, and a closing plenary focused on pedagogical uses of adaptive courseware.

Initiative Type:

Adaptive Learning

ALiS: Adaptive Learning in Statistics Project

admin-annika — Wed, 31 May 2017 04:00:00 +0000

Completion of college-level requirements in the mathematical sciences is one of the most common and vexing impediments to college completion rates, especially for students from lower-income families and underrepresented minorities, where high-school preparation in mathematics is often insufficient. For this reason, important efforts to improve student outcomes in higher education have focused on the application of learning science and use of digital learning platforms to improve the delivery of mathematical sciences content, and on the identification of common learning outcomes and broadly accepted standards in foundational courses—especially introductory statistics. This project builds on this work, as well as on the prior experience of ITHAKA in successfully testing a prototype statistics course with institutions in the ϡȱ�� (ϡȱ��), State University of New York, and the City University of New York.

The goal of the Adaptive Learning in Statistics (ALiS) project is to determine if a flexible learning approach, based on a set of standardized learning outcomes and built on a sophisticated adaptive learning platform (with dynamic authoring capabilities and a rich library of content), can unify content, improve learning outcomes in gateway mathematics courses without increasing costs, and facilitate the transfer of credit between institutions. Our hypothesis is that this strategy can, with the commitment of system-wide faculty and administrative leadership, produce improvements in learning outcomes across a potentially large group of 4-year institutions and community colleges, particularly for at-risk students. Moreover, we hope to show that, especially if one focuses on costs per successful outcome, this approach may result in lower costs for both students and institutions.

The course being developed for the ALiS project is a credit-bearing introductory course in college-level statistics built on a sophisticated adaptive learning platform from Acrobatiq, a company created at Carnegie Mellon University. The course is being designed to meet GAISE standards and to be a multiple pathway option, as developed by the Dana Center at UT Austin and the Carnegie Foundation for the Advancement of Teaching (CFAT) and endorsed by Transforming Post-Secondary Education in Mathematics (TPSE Math). The course also meets the learning outcomes goals for the introductory pathway statistics course recently adopted by the State of ϡȱ��.

The ALiS Project

The ALiS Project has two primary hypotheses. The first is that courseware delivered on a sophisticated adaptive learning platform, as an augmentation to instructor-led classroom instruction, can significantly improve student outcomes without increasing costs. The second is that such a course, with agreed-upon learning outcomes and delivery strategies, can be taken to statewide scale.

The ALiS course is being developed and delivered using the Acrobatiq adaptive learning platform. Acrobatiq is a new company formed by Carnegie Mellon University and is based on the work of the university’s highly successful Open Learning Initiative (OLI). Adaptive learning platforms are computer-based educational systems that dynamically modify the presentation of material in response to student performance—putting the learner at the center of a more personalized learning experience. As students interact with course materials, data are continually collected, analyzed, and reported to a dashboard that allows both students and faculty to closely monitor progress and understand in real time how well students are mastering course learning objectives. With less time needed to deliver content, faculty are freed to focus on struggling students or guide smaller group-based interactions, as well as intervene on a course-wide basis if larger numbers of students are struggling with specific blocks of material and/or basic concepts.

The ALiS Project course was co-developed and tested during 2016-17 by the University of ϡȱ�� College Park (UMCP) and Montgomery College (MC) under the direction of the ALiS Project team.[1] Because many of the community college transfer students at UMCP come from Montgomery College, working together to determine statistics course learning objectives, agree upon delivery strategies, and identify shared instructional materials should facilitate the transfer of these course credits. In this way, these 2-year/4-year collaborations promise to create opportunities to scale this work while improving transfer pathways for ϡȱ�� college students, particularly in mathematics. They also provide valuable professional development opportunities for instructors in both institutions to work together on developing and implementing an innovative course delivery strategy.

Based on the experience gained during limited pre-pilot offerings of the ALiS course during the fall 2016 semester at UMCP and Montgomery, the team is now developing and testing different pedagogical approaches to identify those that are optimally effective for student success.

In 2017-18, with significant funding from a major foundation, our plan is to “scale-up” the delivery of the course and identified pedagogical approaches at additional ϡȱ�� and ϡȱ�� community colleges. A rigorous analysis of student success will be conducted to determine if the adaptive learning technologies and pedagogical approach measurably improve student-learning outcomes. The proposed pilot will compare learning outcomes for students taking ALiS sections of the statistics course (“treatment group”) to students taking standard format/traditional sections of the statistics course (“control group”).

This pilot will take place over the 2017-2018 school year and will involve faculty from the following institutions:

Anne Arundel Community College
Community College of Baltimore County
Frostburg State University
Harford Community College
Montgomery College
Towson University
University of ϡȱ��, Baltimore County
University of ϡȱ��, College Park
Wor-Wic Community College

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[1] In addition to UMCP and MC, the ALiS Project team also includes ITHAKA; the Kirwan Center for Academic Innovation of the ϡȱ�� (ϡȱ��); the Transforming Post-Secondary Education in Mathematics (TPSE Math) as content advisor; Acrobatiq as provider of the adaptive learning platform and advisor on delivery and content; and the Urban Institute as leader of the project assessment team.

Areas of Focus:

Adaptive Learning

Cross Post:

Story

ϡȱ������ Center for Academic Innovation - Adaptive Learning

Adaptive Tools for High-enrollment Online Courses Summit

Areas of Focus:

Cross Post:

ALT-Placement Project

Areas of Focus:

Initiatives Type:

Cross Post:

Call for Participation: ALT-Placement Project

News Type:

Areas of Focus:

Cross Post:

Call for Participation: ALT-Placement Project

Areas of Focus:

Cross Post:

Adaptive Learning

Initiative Type:

ALiS: Adaptive Learning in Statistics Project

Areas of Focus:

Cross Post:

ϡȱ�� Center for Academic Innovation - Adaptive Learning