Data-driven Online Instructor Development

Concurrent Session 1

Session Materials

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Brief Abstract

The online classroom is a source of rich data to inform on-going improvement in online teaching, including this three-pronged strategy to data-driven online instructor development: 1) LMS data
2) Behavior-based student feedback
3) Peer & self assessment

Presenters

Alan Young is the Online Learning Managing Director at Brigham Young University-Idaho, and has been engaged in the strategy and implementation of online learning at BYU-Idaho since 1998. He studied at BYU, Utah State University, and the University of Georgia.

Extended Abstract

This presentation will include examples, and non-examples, from recent experiences and will draw on examples from the audience in order to highlight principles that could be utilized in any institution.
 
This presentation will draw from the following menu of topics, selected according to the background and desires of those in the session:
 
Introduction: a strategy for intentional improvement in online teaching. 

  1. This online instructor development strategy is organized around instructor agency, accountability, and support.
  2. Emphasis on instructor agency creates an environment that encourages innovation and growth.
  3. Instructor accountability provides an opportunity for on-going improvement in key online teaching skills and attitudes.
  4. The right types of support resources enable online instructors as they make decisions about on-going improvement efforts. Rich data is an emerging support resource.

Section 1: LMS data

  1. The LMS gradebook serves as an Instructor dashboard for at-a-glance views of student activity.
  2. LMS data serves as flag to the instructor of struggling students, and succeeding students.
  3. LMS data provides an objective view about instructor activity in the course for self-assessment and peer evaluation. 

Section 2: Student feedback on quality teaching behaviors.

  1. Many evaluation instruments are based on student satisfaction, a helpful but incomplete perspective.
  2. Students are in a unique position to describe the effectiveness of the course and instructor based on specific behaviors.
  3. A new mid-semester evaluation instrument describes specific online teaching behaviors.
  4. Results of the new instrument show clear opportunities for improved online teaching that were not visible in the satisfaction-based instrument.

Section 3: Peer & self assessment

  1. Peer and self-assessment instruments triangulate the quality of the online learning and teaching experience along with LMS data and student feedback.
  2. A new self assessment instrument enables instructors to reflect specifically on the quality of their teaching, and identify specific and incremental opportunities to improve.
  3. A new peer assessment instrument provides an opportunity for a blind peer review, or a trusted colleague, to give feedback on improvement opportunities. The peer assessments occur during on-boarding, including a certification process for new instructors. First year instructors are also given special attention for peer assessment. After the first year, instructors have additional, but less frequent, opportunities for peer assessment.

Wrap-up: Therefore, what? Plans for action and adaptation to other environments

  1. The instruments, models, and principles described are replicable in other institutions and settings.
  2. Discussion of methods for adapting and reusing applicable tools and strategies.

Resources: Links to the instruments and visuals will be provided on the conference web site.