Access Type

Open Access Dissertation

Date of Award

January 2016

Degree Type


Degree Name



Instructional Technology

First Advisor

Ke Zhang



Effect of Expert Modeling on Ill-Structured Problem Solving in an Undergraduate General Education

Honors Course


Minakshi Lahiri

May 2016

Advisor: Dr. Ke Zhang

Major: Instructional Technology

Degree: Doctor of Philosophy

This dissertation research was based on David H. Jonassen’s recommendation that not all problems are the same and different types of problems require different approaches of instruction and scaffolding (Jonassen & Hung, 2008). Jonassen (2011) provided a set of recommended components (problem types, case components, cognitive supports) for designing effective Problem Based Learning Environments (PBLEs).

The purpose of this research was to investigate the effect of using expert modeling of ill-structured problem solving as a scaffolding strategy on undergraduate students’ problem solving outcome. Expert’s analytical guideline to approach and solve an ill structured problem and an example of the expert’s problem solving report was used as scaffold for the problem solving task.

The problem solving performance of the undergraduate students were measured on the three major problem solving learning outcomes as listed below:

i. Ability to define problem

ii. Ability to analyze issues critically and comprehensively

iii. Ability to evaluate proposed solutions/hypotheses to problems

The above mentioned problem solving outcomes and performance scales and categories were defined by a rubric that was developed following the guidelines from the Association for American Colleges and Universities (AACU) problem solving VALUE rubric (Valid Assessment of Learning in Undergraduate Education).

Participants of this study were from 2015 Fall freshmen cohort of Honors College, in a public urban research university in the mid-west of USA. Six Honors College First Year sections participated in this study. Three sections formed the Control group and another three sections formed the Treatment group. The sections were assigned to Control or Treatment group depending on the instructor and was determined with a coin toss. For practical feasibility, three Control Group sections were taught by the same instructor and three Treatment Group sections were taught by same instructor. Students who were less than 18 years of age at the beginning of the fall semester of 2015 were not considered in the study. Total number of participants who qualified for the study, Treatment and Control group combined was 144.

Two groups received an identical problem Task I. 122 participant scores from treatment and control sections combined were analyzed for problem solving Task I to give a baseline problem solving score for the two groups. After Task I, 122 participants were considered for the data analysis of the problem solving task - Task II in this study. There were 54 Participants in the Control Group and 68 participants in the Treatment Group for Task II. The treatment group received the treatment (expert modeling scaffolding) along with Task II and the control group received only the problem solving task - Task II, no scaffold. The problem solving reports from the two groups were graded using the rubric by two reviewers using blind review mechanism for reliability. Reflection responses (optional) were also collected from the treatment group participants on their problem solving experience with the scaffold. Percentage agreement and Cohen’s Kappa were calculated as measures of reliability.

Results of the quantitative data analysis indicated that the treatment group performed significantly better than the control group in the overall problem solving outcome as well as for the components “Ability to define problem” and “Ability to evaluate proposed solutions”. The result was slightly insignificant for the category “Analyze issues critically and comprehensively”. Qualitative data analysis of the treatment group reflection responses were highly positive and indicated that the learners perceived that the scaffold strategy was beneficial for them and that they learned from the experts analytical guidelines. The participants thought that the expert modeling benefited them by providing a useful tool and framework that they could use in future for other similar problem solving situations; the scaffolding strategy helped them organize and structure the information and helped them follow expert’s strategies on critical thinking and problem solving while approaching and working on the problem solving task.