International Engineering Education Conference - Turkey's Vision 2023 Conference Series - Atılım University

Workshops

Workshop #3

“I Can Do It”: Understanding and Measuring College Students’ Engineering Self-Efficacy

The goal of this interactive workshop is to help engineering faculty members and assessment coordinators understand the importance of engineering self-efficacy for improving college student learning, motivation, retention, and achievement.  It has been nearly a decade since Ponton et. al. (2001) urged engineering faculty and researchers to pay attention to the construct of self-efficacy.  Yet, the field still lacks useful, valid, and reliable measures for doing so.  A scientist would never embark upon a research program using an uncalibrated instrument – likewise rigorous, calibrated measurement tools are required to measure student self-efficacy.  Thus, we plan to assist workshop participants begin the task of developing items and scales to measure engineering self-efficacy.
The need for developing future engineers who are highly motivated is acknowledged by ABET, Inc., which is the accrediting body for engineering programs in higher education.  ABET, Inc. currently accredits some 2,700 programs at more than 550 colleges and universities in the United States. Within the ABET standards we see the set of program outcomes that requires engineering programs to demonstrate their students attain “a recognition of the need for, and an ability to engage in life-long learning” (ABET Criteria 3: Standard (i)).  ABET is not alone in suggesting college graduates should become life-long learners who are self-motivated, self-directed, and can regulate their own learning and performance.  Researchers in higher education have also argued that developing motivated, self-directed learners should be stated as an important and explicit outcome in higher education (Garrison & Archer, 2000; McCombs & Marzano, 1990; Weinstein & Van Matter Stone, 1993).  Although there may be general agreement that there is a need for developing future engineers who are highly motivated, self-regulating, and committed to becoming a “life long” learner, the field of engineering education lacks specific theoretical frameworks with accompanying measurement tools for measuring specific aspects of student motivation to learn.  In response to this need, we aim to develop a battery of engineering self-efficacy scales that can be used to measure an important component of achievement motivation.

Defining Self-Efficacy
Self-efficacy beliefs are personal judgments about one’s generative capability for cognitive, behavioral, social, and emotional actions.  Bandura (1982, 1986) differentiated two types of expectancies that serve important mediating roles in understanding self-efficacy, as shown in the figure immediately below.

Two Types of Self-Efficacy Beliefs

By their very nature, self-efficacy beliefs are highly subjective and individualized.  Students’ self-efficacy beliefs vary depending on their academic background and chosen major within engineering.  For example, we would predict a high amount of variability in student responses for the following self-efficacy items:

  •  “I can use the Vector-Matrix class to write a program that solves a system of linear equations using Gauss Seidel method.”
  •  “I can use a Storage-Detention flood routing (Pul’s algorithm) to design a flood detention basin.”

The Self-Efficacy Approach to College Student Recruitment and Retention
Because self-efficacy beliefs influence the types of behaviors people will initiate and maintain they are paramount to issues of student recruitment and retention.  Student’s beliefs in their personal efficacy play an important role in how they organize, create, and manage the environment that affects their academic and career pathways.  For example, a first-year student might believe “I want to be an engineer”, however; if he/she does not believe “I can do calculus” it is unlikely the student will initiate the actions necessary to become an engineering major.  We know that students engage in activities in which they feel competent and confident and avoid those in which they do not.  Moreover, the stronger their self-efficacy perceptions, the harder they will try when faced with adversity. As a result of these influences, self-efficacy beliefs can strongly determine a student’s level of academic performance (Bandura, 1997).

Workshop Details

Learning objectives

Workshop participants will learn the following in this session:

  • An understanding of the “will and skill” model of self-regulated learning.
  • An understanding of the basic tenants underlying Albert Bandura’s Social Cognitive theory and its implications for engineering education.
  • An understanding of the self-efficacy construct.
  • An awareness of what self-efficacy predicts for college student learning and performance.
  • An appreciation of why it is important to measure self-efficacy.
  • The ability to contrast self-efficacy to other “self” constructs, such as self-esteem and self-concept.
  • The ability to contrast self-regulated learning models to “learning styles” models.
  • The ability to write self-efficacy items for their respective engineering area.
  • Strategies for how self-efficacy scales can be used to improve college student learning and motivation.
  • Strategies for how to design college courses to enhance students’ engineering self-efficacy.
  • Ideas for how to embed measures of self-efficacy into accreditation, assessment, and program evaluation activities.

Justification for a pre-conference

This session is designed to be a 2 ½ hour interactive workshop that will allow for maximum discussion about teaching practices and student motivation. Participants will be involved in writing self-efficacy scale items and will have the opportunity to get feedback from other participants regarding their draft self-efficacy items. Discussions will occur in pairs and small groups.

How will the workshop be conducted?

The workshop will begin with a very brief introduction to Social Cognitive Theory, self-regulated learning, achievement motivation, and the self-efficacy construct. The presenters will briefly review the current literature on engineering self-efficacy and provide an overview of available scales for measuring engineering self-efficacy. The presenters will share specific examples of how to measure self-efficacy within the following engineering areas: civil, electrical, and mechanical. Participants will actually write self-efficacy items and share ideas for how they can embed self-efficacy measures into their teaching and assessment activities. The presenters will share ideas for how to include self-efficacy measures in a program evaluation and accreditation activities. Given the international focus of the conference, participants will be exposed to self-efficacy literature and research from a global perspective. We will discuss the cultural implications of understanding and measuring self-efficacy.

Core issues

  • Pedagogical Approaches and Assessment Methods in Engineering Education 
  • Future Engineers, How should they be?
  • Accreditation in Engineering Education

Audiences

This workshop is designed for faculty members, assessment coordinators, and doctoral students interested in the study of college student achievement motivation.

Speaker Details

Gypsy M. Denzine, Ph.D.
Associate Dean and Professor of Educational Psychology
College of Education, Northern Arizona University
PO Box 5774 NAU, USA
Flagstaff, AZ 86001
Ph. 928-523-9211
Fax. 928-523-9284
Email: Gypsy.Denzine@nau.edu

Dr. Denzine has been working with engineering faculty for the past four years to measure self-efficacy to improve student learning and gather evidence for accreditation activities. She will lead the workshop discussion on the theoretical overview, the introduction to Social Cognitive Theory, and the procedures involved in effectively measuring self-efficacy to improve college student learning, motivation, and academic performance. Each of the presenters below will briefly share their experiences in measuring self-efficacy and provide examples of how they have revised their teaching and/or assessment activities as a result of having information about their students’ engineering self-efficacy.

Heidi Feigenbaum, Ph.D.
Assistant Professor of Mechanical Engineering
College of Engineering, Forestry, and Natural Sciences
Northern Arizona University
Flagstaff, AZ 86001, USA
Email: Heidi.Feigenbaum@nau.edu

Joshua Hewes, Ph.D.
Assistant Professor of Civil Engineering
College of Engineering, Forestry, and Natural Sciences
Northern Arizona University
Flagstaff, AZ 86001, USA
Email: Joshua.Hewes@nau.edu

Eric Wang, Ph.D.
Associate Professor of Mechanical Engineering
College of Engineering
University of Nevada, Reno
Reno, NV 89557
Reno, NV, 89557, USA
Email: Elwang@unr.edu

Niranjan Venkatraman, Ph.D.
Assistant Professor of Electrical Engineering
College of Engineering, Forestry, and Natural Sciences
Northern Arizona University
Flagstaff, AZ 86001, USA
Email: Niranjan.Venkatraman@nau.edu