Instructional Design for Online Learning:Are Pre-Service Teachers Prepared?

VERA S. WEBER

Topic

This study seeks to understand and describe how college

and universities offer instructional design within their

undergraduate teacher education programs to meet the

growing demand for online learning in K-12 school systems.

Statement of the Problem The K-12 public school system is creating a high demand for

courses offered through online learning (Watson, Murin, Vashaw, Gemin, & Rapp, 2013).

School systems are turning to the knowledge of subject matter experts, or classroom teachers in this case, to create and design online learning environments (Project Tomorrow, 2011).

There is a need for teachers who have knowledge and skills in instructional design (Picciano & Seaman, 2009)

Teacher education programs will need to equip all teachers with the ability to design, deliver, and support K-12 online learning (Barbour, Siko, Gross, & Waddell, 2013)

Purpose

The purpose of the proposed qualitative, multi-case study

is to understand and describe undergraduate educational

programs offered through Midwestern colleges and

universities in order to determine how these programs

strive to prepare pre-service teachers for designing online

learning environments that implement instructional

design principles, models, and strategies.

Research Questions

How do pre-service teachers in undergraduate preparatory

programs learn instructional design competencies,

including knowledge, skills, and attitudes needed to deliver

online learning programs?

What are the titles of programs, specific courses, and

objectives within courses in undergraduate teacher

preparatory programs that address instructional design

theory, models, or strategies and specifically their

application to online learning?

Theories Supporting this Research

Instructional Design Theory: A prescriptive theory that recommends a specific action to achieve the goal of instruction (Christensen & Osguthorpe, 2004; Smith & Ragan, 2005)

Constructivist Design Theory: A learning theory that is based on three principles 1) learning comes from interpretations of personal

experiences which

2) exist in realistic and relevant situations and

3) include explorations of multiple perspectives (Richey, Klein, & Tracey, 2011).

Qualitative, Multi-Case Study

Yin, R. K. (2009). Case study research design and methods, (4th ed.). Los Angeles, CA: Sage

Yin’s model for conducting case study research

Prepare

Collect

AnalyzeShare

DesignPlan

Qualitative, Multi-Case Study

Yin, R. K. (2009). Case study research design and methods, (4th ed.). Los Angeles, CA: Sage

Yin’s model for conducting case study research

Field Test Documents

IRB Approval

Multiple sources of evidence

Organize data Maintain chain of evidence

Rely on Theory and Literature

Use an analytic

techniqueDisplay data

Review and Re-writeDisplay

evidenceCompose

textual and visual

materials

Define Unit of AnalysisDevelop

Theoretical PropositionsDefine Case

Study Quality

Scientific Merit Review

Plan

Research Design Target Population: Pre-service Teacher Preparatory programs

Sampling method: Purposive

Sample Size: 3-5 teacher education programs in Minnesota

Candidate Pool: 4-5 participants from each research site

Maximum Variation Strategy: Privately or Publicly funded institutions in diverse geographical locations

Recruitment: Letters to Department Chairs of Minnesota Teacher Education Programs, Snowball Strategy, Posting a Recruitment Flyer

Data Collection

Feedback from Pre-Qualifying Questionnaire

Face-to-face or telephone interviews recorded using Audacity or similar software, transcribed, and reviewed for accuracy by participants

Documents: syllabi, textbooks, course catalogs

Physical Artifacts from institution’s website

Optional, self-administered classroom observation by faculty member

Sources of Evidence for triangulation

Triangulated Sources of Evidence

Interviews

Information from the institution’s website

Faculty

Pre-Service Students

Former Students working in an online environment

Physical Artifacts

Examples from student projects

Education Department Chair

Optional, Self-administered classroom observations

DocumentsCourse Catalogs

Syllabi

Textbooks

Course Materials

Data AnalysisWithin Case

Yin’s (2011) Five Phase Process for Analysis

Compile Data – organizing field notes and other coded data collected for each case

Dissemble Data – Develop categories and themes and reorganize coded data.

Reassembling Data - Creating display matrices or arrays

Interpreting Data - Analysis

Concluding – Making conclusions about the data and findings

Data Analysis: Cross Case Analysis

Assemble analyses from individual case studies

Develop display matrices within each case study and across cases (Miles & Huberman, 1994)

Examine the emerging categories and themes based on the theoretical proposition of the case study (Yin, 2009)

Use Nvivo 10 database software to organize data collected from transcribed interviews, self-administered observations, documents, and website information

Data

Colle

ctio

n P

lan

Goal: Walk in Commencement August 16, 2014 End of Spring Quarter: June 13, 2014

Finalize Chapter 3

Complete Data Collection and Analysis

Work on Chapters 4 & 5 during break

Summer Quarter First Draft of Chapters 4 & 5 submitted first week

of Summer Quarter

Apply for graduation

Complete Chapters 4 & 5

Gain Mentor Approval for Chapter 3, 4, & 5 (Milestone 9)

Questions

References

Watson, J., Murin, A., Vashaw, L., Gemin, B., & Rapp, C. (2011). Keeping pace with K-12 online learning:

An annual review of policy and practice. Sammamish, WA: Evergreen Education Group

Project Tomorrow. (2011). Learning in the 21st century: 2011 trends update. Irvine, CA: Project Retrieved from http://www.blackboard.com/CMSPages/GetFile.aspx?guid=f68cca85-a863-43c9-9dbd-8ff4439b87b3Tomorrow.

Picciano, A. G., & Seaman, J. (2009). K-12 online learning. Retrieved from http://155.48.10.202/Academics/Documents/babson-survey-research-group/k-12-online-learning-2008.pdf

Barbour, M. K., Siko, J., Gross, E., & Waddell, K. (2013). Virtually unprepared: Examining the preparation

of K-12 online teachers. In R. Hartshorne, T. Heafner, & T. Petty (Eds.), Teacher education programs and online learning tools: Innovations in teacher preparation (pp. 60-81). Hershey, PA: Information Science Reference. doi:10.4018/978-1-4666-1906-7.ch004

Christensen, T. K., & Osguthorpe, R. T. (2004). How do instructional-design practitioners make instructional-

strategy decisions? Performance Improvement Quarterly, 17(3), 45-65. doi:10.1111/j.1937-8327.2004.tb00313.x

Smith, P. L., & Ragan, T. J. (2005). Instructional design. Hoboken, NJ: John Wiley & Sons.

Richey, R. C., Klein, J. D., & Tracey, M. W. (2011). The instructional design knowledge base. New York, NY:

Routledge

Yin, R. K. (2009). Case study research design and methods, (4th ed.). Los Angeles, CA: Sage

Miles, M. B. & Huberman, A. M. (1994). Qualitative Data Analysis (2nd ed.). Thousand Oaks, CA: Sage.