interaction equivalency in self-paced learning environments

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Interaction equivalency in self- paced online learning environments: An exploration of learner preferences Dissertation Proposal Jason F. Rhode 9/10/2007

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Page 1: Interaction Equivalency in Self-Paced Learning Environments

Interaction equivalency in self-

paced online learning

environments: An exploration of learner

preferences

Dissertation Proposal

Jason F. Rhode

9/10/2007

Page 2: Interaction Equivalency in Self-Paced Learning Environments

Jason F. Rhode

• Ph.D. candidate, Capella University

• Specialization: Instructional Design for Online Learning

Page 3: Interaction Equivalency in Self-Paced Learning Environments

Introduction

interaction

self-paced learning

emerging communication approaches

Page 4: Interaction Equivalency in Self-Paced Learning Environments

Background

• Substance and function of online interactions varies

• Interaction is essential for a quality learning experience

• Unanswered questions concerning learners’ interaction preferences and degree in which interactions are perceived to be equivalent

Page 5: Interaction Equivalency in Self-Paced Learning Environments

Statement of the Problem

• Interaction identified as a key element to successful online learning programs

• Little empirical evidence currently exists as to the value that learners place upon various types of interactions in a self-paced learning environment

Page 6: Interaction Equivalency in Self-Paced Learning Environments

Types of Interactions

Page 7: Interaction Equivalency in Self-Paced Learning Environments

Interaction Equivalency Theorem

Page 8: Interaction Equivalency in Self-Paced Learning Environments

Purpose of the Study

• Expand upon previous research advocating for purposeful design of interaction

• Examine the composition of the online learning experience of adult learners in self-paced learning environment

• Explore what forms of interaction self-paced online learners value most as well as what affect such interactions have on their overall learning experience

Page 9: Interaction Equivalency in Self-Paced Learning Environments

Research Questions

1. What forms of interaction do adult learners engage in most in self-paced online courses?

• What forms of interaction do adult learners value most in self-paced online courses?

• What forms of interaction do online adult learners identify as equivalent in self-paced online courses?

• What impact does interaction have on the self-paced online learning experience?

Page 10: Interaction Equivalency in Self-Paced Learning Environments

Research Design

• Phenomenological methodology

• Semi-structured in-depth interviews conducted near the conclusion of the course

Page 11: Interaction Equivalency in Self-Paced Learning Environments

Sampling Design

• Participants– Online adult learners enrolled in a fully-online

professional development certificate program offered by Valley Forge Christian College

• Participant selection– Convenience sample: all learners (n=13) in Sept.

2007 section of “Advanced Web Communications” course invited to participate

Page 12: Interaction Equivalency in Self-Paced Learning Environments

Measures

• Semi-structured, in-depth interviews to be conducted over the phone, each approx. 1 hr. in length

• Questions will address 3 main types of interaction and formal vs. informal nature of such interactions

• Interviews recorded and transcripts coded for

Page 13: Interaction Equivalency in Self-Paced Learning Environments

Data Collection Procedures

• Approval from Capella University IRB and VFCC Academic Affairs

• Instrument and protocol to be pilot tested

• Interviews conducted via phone and recorded, transcribed, and coded

• Interview transcripts sent to interviewees to confirm accuracy prior to coding

Page 14: Interaction Equivalency in Self-Paced Learning Environments

Ethical Issues

• Learners have no obligation to participate

• Interview data stored securely using assigned id codes in place of participant names

• Pseudo names used in place of actual names

Page 15: Interaction Equivalency in Self-Paced Learning Environments

Data Analysis Procedures

• Identify emergent themes from the data that will serve as foundational schema for further data organization and analysis

Page 16: Interaction Equivalency in Self-Paced Learning Environments

Expected Findings

• It is expected that one or more types of interaction will surface as being preferred for adult learners

• Learners may recognize certain interactions as equivalent