Examining Issues of Working with At-Risk Learners in Online Environments (Cira B)
Cathy Cavanaugh, University of Florida
Daryl Diamond, Broward County Public Schools
Leanna Archambault, Arizona State University
Michael Barbour, Wayne State University

To better understand how online programs are dealing with students who have been identified as at-risk, the iNACOL Research Committee gathered a sampling of K-12 online schools currently working with at-risk student populations to examine specific strategies as well as delivery and design methods used to assist at-risk student populations. This session will bring together a panel of authors to share and discuss key findings from "An Exploration of At-Risk Learners and Online Education."

The PowerPoint presentation:

The actual research brief:

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Notes by Marcel Kielkucki--Director of HS Completion Programs--Kirkwood Community College (
Breakout Session1—An Exploration of At-Risk Learners and Online Education—Panel Discussion by Barbour, Archambault, Diamond, and Cavanaugh
Session is focused on the research committee report in participant packets. Refer to that document if you have further questions.
The research committee tries to bring information from researchers to practitioners, and to provide research briefs.
Don’t take these as empirical research, just a first attempt. It’s not a set of best practices, or a road map, or reliable and valid. Problem is there is not a lot of research out there.
It is a first look at how at-risk students are being surveyed in programs, based on data collected on some individual school programs. 14 case studies of 22 programs, and a starting point for future investigations.
Working with At-Risk Student Populations sub portion
-At risk is a loaded term. At risk is one likely to fail at school—dropping out—either for academic or personal/family reasons. (Can include a wide range of students as a result.)
The methodology was to create a web-based survey distributed to programs via email. Results came from 14 states, and British Columbia and got 22 program responses, primarily cyber-charters
Survey results showed that 29% of programs had 25-50% of at risk students, and 25% had over 75% of at-risk students.
Key strategies were use of supportive faculty/staff, individualizing instruction, and instructional practices/strategies
Staff—there’s a need for ongoing communication among all involved with at-risk students, and faculty/staff need to take a direct role in overseeing student progress and success throughout the program (idea of a student success coach)
Individualizing Instruction—Maximize the use of technology/curriculum. Use one-on-one and small group instruction for key concepts, and use things such as My Reading Coach, Lexia for reading comprehension and fluency. (Do we have access to my reading coach via learning services?)
Strategies—Key focus was mastery learning—focus is on learning rather than performance. Allows them to revise work until they meet the targeted outcome, and online classes allow flexibility for those meeting expanded learning time to master the content.
School level interventions can included, direct communication among teachers, mentors, learning coaches, students, and families. For example, have direct communication with students/parents on expectations. Need more teacher-student contact to support struggling students, and accountability to ensure communication occurs.
It’s also important to identify at-risk students as early as possible to provide the necessary support systems, and then you can implement strategies right away.
Those who use these strategies saw increased completion rates from those who were not successful in f2f settings, higher graduation rates, less attrition, and closer ties between students and staff.
Implications: there’s a need for PD for online teachers, tutors, facilitators, etc., improve comprehensive data systems to inform and guide teaching practices, increased accessibility to online courses, and research that is focused on learning environments that support at-risk students.
Identified Trends—Increasing mentoring and tutoring, using data to evaluate student needs, screen, identify, and evaluate at-risk factors, and instructional practices.
Some pre-screening tools: Lexile framework—using lexile scores, LASSI (Learning and Study Strategies Inventory), and Response to Intervention
Ways to identify At-Risk Students: enrollment questionnaire, teacher referral, local school registration for students retaking courses, recommendation from school districts, intake interviews, consultations with parents and school officials, testing, a red-flag process (attendance, progress, IEP, etc.) ongoing modifications done depending on level of student performance, and intervention specialist sent to work with students
Practices could include strategies such as synchronous activities, web conferences, some f2f meetings, use the one-at-a-time course approach, student assistance program, case-management system, chunking student work, flexible learning environments, granting extensions, and building in computer literacy skills.
There is a contrast on what it takes to be successful in online courses with the at-risk student traits.
We need to develop specific programs within virtual schools to cater to non-traditional distance learning students and at-risk students. If not, online learning can become out of reach for this population.
Successful at risk and ESE students depend on teachers who understand their needs and use strategies to differentiate, depend on course and program structures that provide flexibility, time, and attention, and depend on school supports to fill academic and other gaps. (Nikki Davis/ISU research)
Benefit from 5c’s: Connect, Climate, Control, Curriculum, and Care
-Connect practices in virtual schools. Have a senior seminar course to help students with goal-setting and planning for life after high school (some research showing career planning needs to be done in Middle School instead, so this is life course)
-Prepare students for success in a technology-based economy (we need to teach to be users not consumers!)
-Emphasize life skills and work Readiness
-Partner with community organizations to provide trade skills to students (role of the community colleges and we are in dire need here!)
-Focus on safety and respect (allow for failure)
-Give weekly data reports to guide teachers in their student meeting, etc.
-A team approach that includes instructional coaches and intervention teacher
-Small group intervention classes or one-to-one interventions, based on each student’s academic data.
-Decreasing absence, truancy, and other behavioral issues by identifying causes of these issues and developing action plans to correct them
-A RTI program and a life skills program to meet behavioral and emotional needs of students
Curriculum (easiest to accomplish in online environment)
-Grouping students to provide specific skills and strategies for academic success (difficult for open enrollment models)
-Developing differentiated scaffolds for each student, monitored by a teacher-mentor, and supported by an orientation in time management and task prioritizing. Most orientations do not deal with soft skills and instead focus on the program itself. However, something on this level could be developed and utilized by many programs as these are skills we all need.
-Mentoring for student success
-Positive communications between teachers, students, and parents—give encouragement now and then rather than all being negative ones.
-Policies to ensure regular, proactive communication.
-How do you have the lunchroom/hallway conversations in online environments?
To help teachers, we need specific PD that will be discussed at a session tomorrow afternoon in another session. We also need to have orientation for those who work in these situations as well.
Four areas are identified in the report for future research: how identification of students affect attrition and completion rates, and what do programs do if they know their students are at-risk. Also, they want to look at assessment and prediction tools, models, and instruments used to remediate students to ensure online success.
The largest block of online learners are currently being ignored.
Also need to design specific delivery models that have evidence of improving at-risk students success (AP models won’t work for At-risk students)
Look also at the factors that facilitate high levels of student engagement and contribute to positive learning communicates in virtual environments.

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