Stoplights for student success

Slides:



Advertisements
Similar presentations
Building an Early Warning System for New Transfer Students Marcy Esler Director of Student Retention State University of New York The College at Brockport.
Advertisements

Learning Analytics: On the Way to Smart Education Dr. Griff Richards Athabasca University Moscow, 08 October 2012.
1 Predicting Success and Risk: Multi-spell Analyses of Student Graduation, Departure and Return Roy Mathew Director Center for Institutional Evaluation.
CSIS-385: Algorithm Analysis ► I am Dr. Breimer ► Br-Eye-mer ► I like ► Office hours: 1:35-2:30 everyday ► Drop by randomly at your own risk.
FREQUENTLY ASKED QUESTIONS STUDENT’S HAVE ABOUT ETUDES AND THEIR ONLINE COURSES Students want to know…. Jill Brown-Counselor.
Redesign of Beginning and Intermediate Algebra Lessons Learned Cheryl J. McAllister Laurie W. Overmann Pradeep Singh Southeast Missouri State University.
Student Forum March5, pm - Collaborate Students will share their thoughts on topics including: --experiences with online courses --ways instructors.
Supporting Campus-wide Culture Change at Northeast Wisconsin Technical College Green Bay, Wisconsin.
PEER ASSISTED STUDYING An Untapped Resource for Student Success Presented By Susan Easton
First Year Intervention Learning Resources Center UMBC.
© 2015 Jenzabar, Inc. Increase Your Prediction Accuracy and Achieve Maximum Student Success Paul Gore Xavier University Burt Rubenstein.
Research Participation Program (RPP). For students: – An opportunity to experience primary research in psychology, organizational behavior, economics,
Online Orientation Professor: María L. Villagómez Contact Information: Office: BLDG (1031U) Telephone#:
Building Capacity for Analytics within the Academic Environment John P. Campbell Purdue University.
EARLY ALERT GRADE PROPOSAL University Senate, November 2012.
Early Alert March 19, Early Alert Over the past year and a half, the Early Alert Committee has developed and piloted a proposed next step to mid-semester.
Retention for Online Learners. 2  Industry Research  Identifying Students at Risk  Making an Impact Agenda:
SI, SLA, and YOU Your guide to CSU’s two new services for students.
The ABLE project: How do we put what we have learnt from learning analytics into practice Tinne De Laet, Head of Tutorial Services, Engineering Science,
EARN Early Alert Retention Network Powered by: UTSA’s Academic Early Alert System.
Creating a Comprehensive Early Warning System to Further Student Success and Retention Shane Hammond CCLA June, 2007.
Starfish Training Minot State University
Development of Self-Determination and Social Skills of College-Bound Students with Visual Impairments Report on an Intervention Program Designed to Improve.
OAAI: Deploying an Open Ecosystem for Learning Analytics
Kudos for Starfish! Pilot Review and Plans for UC Advising Conference
Frequently asked questions
Introductions Office of Completion and Student Success
Moving forward into a new generation of teaching and learning
Improving Retention with Technology
Creating a Blueprint For Student Equity and Student Success, Part 2
Developing an early warning system combined with dynamic LMS data
Marla M. Bell Associate Dean of Student Success
Scheduled to begin Fall 2017 PENDING final University approval
Transfer and New Student GROUP ADVISING
USFSP Persistence and Completion
Online Course Design: Is the Conversation Over?
(includes online “demo” video)
Welcome to General Biology II!
Biochemistry and Molecular Biology
Database Design and Implementation
Academic Performance Evaluation for B.COM/BIB Students
Rockridge Secondary School
WELCOME BMB MAJORS Freshman Year Advising Meeting
Welcome to Biology 101! Please pick up a syllabus (if you don’t have one yet) and a clicker at the front desk. You will need to rent a clicker from.
2018 Student Success Summit
Student Data Analytics
A confidential listening and information service
Starfish Faculty Training How to Raise Flags and Kudos
CS 6020 Advanced Computer Architecture
Assessment Day 2017 New Student Experience Presented by Jenny Lee
Welcome to Biology 101! Please pick up a syllabus (if you don’t have one yet) and a clicker at the front desk. You will need to rent a clicker from.
Spanish 120, 110, and 111, Elementary Spanish I
Where We Began – Summer 2013 Campus Strategic Plan
The Academic Alert System: Fall 2007 Report
Online HCA Overview.
Welcome to the First-Year Experience!
for Instructors and Roster Contacts
Lecture 1a- Introduction
Online HCA Overview.
Academic Performance Evaluation for BCOM/BIB Students
Online HCA Overview.
Assessment Day 2017 New Student Experience Presented by Jenny Lee
Impact of AB 705 and Guided Pathways on Part-Time Faculty
Online HCA Overview.
COURSE PLANNING IN AN OPEN ENROLLMENT ENVIRONMENT
Lecture 1a- Introduction
UNIVERSITY TOP 10 Understanding What to Expect as a Future University Student
DSU Online Teaching Certification
Starfish Training Erie Community College
Lecture 1 6 September 2019   Course syllabus, food guide and exercise guide Notes and other information are on:
Presentation transcript:

Stoplights for student success SIGNALS Stoplights for student success

Agenda Student performance tracking Stoplights - Signals Context – John Campbell’s model Process – what it could involve Overview – how it is implemented now Pilot results & feedback Sneak Preview How to get started

Student Performance Tracking Tracking progress Running grade totals Calculating midterm grades Class grade statistics Available methods Blackboard grade book Blackboard tracking data

What is Signals Signals detects early warning signs and provides interventions for students who may not be performing to the best of their abilities before they reach a critical point in their class.

Project Context Model based on J.P.Campbell’s (2007) work Goals Identify at-risk students early Intervene early Improve chances of success Goals Creation of independent learners Retention to in-demand degrees Improved student experience Preservation of marketing/recruitment dollars

Signals – The Process Predicted Student Success Algorithm Effort Tracking Data Grades Help Seeking Behavior Intervene to determine “risk-groups” Communicate students’ performance

Signals - Overview Combines predictive modeling with data- mining from Blackboard Interventions are based on Grades and Effort Each student is assigned an individual “risk- group” high likelihood of failing the course potential problem with succeeding in course high likelihood of success in the course

Signals – Overview contd. Communicating students’ performance Sending Intervention emails Personal emails to individuals Mass class emails grouped by risk-groups Releasing Stoplights in Blackboard Providing resources for improvement - 1-1 meetings - online help/resources - mentors - etc.

Pilot Study Results – Spring 09 900 students in Biology and Math courses Higher levels of help-seeking behavior Higher level of Bs and Cs and lower levels of Ds and Fs More drops and withdrawals Greatest success with moderate risk students

Risk Groups Most remained “at risk”. Still unlikely to take advantage of resources. Majority were able to leave the “at risk” status – as long as feedback continued. More likely to take advantage of resources. Least affected. Instructors can still send positive feedback.

Feedback from Students “Your message was a ‘kick in the butt’ that woke me up.” “Really appreciate knowing how I’m doing in the class before I get too far into the course.” “This biology lab is the hardest I’ve ever taken, but your message let me know that I need to get more help. Also, I can see that this lab is helping me in my biology lecture course and in my chemistry lab.”

Feedback from Instructors “"I have not heard first hand, nor anecdotally that students don’t like these messages; I have not heard one complaint.  Actually, I gave a talk last spring and there were students in the audience because they seemingly had a class assignment to go to my talk, and in their evaluation of my talk they wrote, I wish I had this [messages] in all my classes.“ Dr. Laurie Iten, Associate Professor of Biology

Why do it? Signals communicates directly to students facilitating faculty/student communication Provides resources to help students meet demands of their classes Early academic success for students Students like the help

How it works Works in three different ways Provides real-time feedback Intervention starts early Frequent and ongoing feedback

Fall 2009: 9-10,000 students Class No. of Students CHEM 111 2600 1078 STAT 301 900 SPAN 101 300 SPAN 102 500 MA 154 MA 153 600 AGRY 105 60 BIOL 195 150 CDFS 210 455 ENGR 126 1400 IT 345 80 GS 101

Sneak Preview

Who can use this application? Signals is open to all instructors and can be used for any course Specifically targeted to large enrollment gateway courses Must use Blackboard Vista in WL academic institution Future – looking for ways to include regional campuses

How do I get involved? Project Contact Kim Arnold - kimarnold@purdue.edu Signals Support Contact IDC – tlt-consulting@purdue.edu; 496-3257 Join the listserv signals@lists.purdue.edu Look for more information in Purdue Today