Investigating the Teaching Concerns of Engineering Educators

October 2007 Journal of Engineering Education 295

Investigating the Teaching Concerns of Engineering Educators

JENNIFER TURNS

Department of Technical CommunicationUniversity of Washington

MATT ELIOT


ROXANE NEAL


ANGELA LINSE

Schreyer Institute for Teaching ExcellencePennsylvania State University

ABSTRACT

The teaching concerns of engineering educators offer one lensfor thinking about how to support engineering educators’efforts to improve their teaching. In this study, we collectednarrative accounts of teaching consultations between engi-neering educators and an instructional consultant. Transcriptsof these accounts were coded for individual teaching concerns,which were then interpreted from the perspective of existingmodels and also aggregated into themes. We discuss our find-ings by using them to highlight ways in which engineeringeducators are already thinking effectively, to suggest how theadoption of innovation and professional problem-solving canserve as promising frameworks for thinking about teachingactivity, and to suggest that additional research on engineeringteaching take advantage of distributed cognition models totruly understand how our students are taught.

Keywords: Faculty development, Teaching concerns

I. INTRODUCTION

Teaching concerns are a promising lens for exploring

teaching activity. While teaching concerns research is an

already established approach for helping K-12 educators to

improve their teaching, the opportunity exists to bring this

line of thought to the challenges of improving engineering

teaching and speeding up the processes of change. This study

offers a beginning point for understanding the teaching

concerns of engineering educators at a Research Extensive

university. Using instructional consultation as our context,

we investigated the concerns expressed by individual

educators and teaching-related groups during the consulta-

tion process.

We were drawn to teaching concerns because of the histori-

cal precedent associated with this body of scholarship, the

promise of using concerns as a tool for explaining and even pre-

dicting difficulties and resistances, and the related issue of the

strong link between this body of scholarship and the practical

goal of helping educators improve their teaching (through both

formal education and professional development). The engineer-

ing education community is increasingly recognizing the impor-

tance of proactively helping engineering educators advance their

teaching effectiveness [1]. A number of valuable resources are

currently available, ranging from individual instructional con-

sultations to larger workshops on teaching skills. Furthermore,

engineering education researchers are actively seeking to prove

the effectiveness of specific teaching strategies. However, such

efforts might have greater success if we as a community knew

more about the actual needs of engineering educators. In this

light, the investigation of teaching concerns represents an initial

form of needs analysis. We believe that such information can

help a range of stakeholders in the engineering education

process to anticipate concerns that educators will have, and to

develop strategies to address and manage those concerns.

Our study approach addressed one of the challenges of in-

vestigating teaching concerns (indeed a challenge of any form

needs analysis)—the issue of when and how to get at the needs.

In the context of engineering education, teaching is typically a

private individual activity, thus making it difficult to get the

needs documented. This research stemmed from a unique op-

portunity to capture information about teaching concerns soon

after they were mentioned by educators. In particular, we de-

briefed an instructional consultant after interactions with indi-

vidual educators and teaching-related groups. This approach

represented an opportunity to identify engineering educator

concerns associated with “lived” teaching challenges rather

than concerns generally reported by instructors in a decontex-

tualized situation.

The remainder of the paper is organized as follows. The next

section reviews research on teaching concerns as well as research

on the instructional consultation process, the context we used

for studying teaching concerns. In the Method section, we de-

scribe our means for collecting data in the context of instruc-

tional consulting and our approach for systematically reducing

the data in order to both identify the underlying concerns and

address research questions related to those concerns. The

Results section focuses on a characterization of the teaching

concerns relative to two prevalent teaching concern theories (a

deductive analysis) and in terms of emergent themes (an

inductive analysis). In the Discussion, we relate these findings

to three broad issues.

II. BRINGING TEACHING CONCERNS TO

ENGINEERING EDUCATION

Teaching concerns have been defined as comprising “the

questions, uncertainties and possible resistance that teachers may

have in response to new situations and/or changing demands” [2].

The majority of this research to date has focused on K-12 environ-

ments. The differences between the K-12 and engineering

education contexts suggest that an exploratory approach to investi-

gating teaching concerns in engineering education would be both

revealing and beneficial.

A. Prior Work on Teaching ConcernsTeaching concerns research has its roots in teacher education

and teacher professional development. Work in this field seeks

to (a) understand and categorize the types of concerns that edu-

cators encounter when learning to teach as well as when engaged

in teaching practice, (b) confirm theoretical propositions about

the link between the relative presence of different types of teach-

ing concerns and a teacher’s level of experience, and (c) explore

teacher preparation and teacher professional development

strategies that characterize teachers in terms of their concerns.

Interest in teaching concerns theory has been tightly tied with

the notion that teacher education informed by concerns shared

by teachers will be more effective than one that fails to consider

common teaching concerns.

Frances Fuller is the point of origin for the work on using

teaching concerns as a lens into the development of teaching

skill. In her germinal study almost four decades ago, Fuller [3]

collected information on the concerns of pre-service teachers via

open-ended prompts and found that these concerns could be

grouped into three categories: survival, situation, and pupil. Fur-

ther, she noted that beginning pre-service teachers had more

survival concerns while those teachers farther along had more

pupil concerns. This observation became the basis for concerns

theory, the understanding that concerns about teaching evolve

as the teacher develops his or her teaching skill.

Over time, these three categories became known as Self, Task,

and Impact and the general theory came to be understood as a

developmental stage theory. According to Borich and Tombari

[4, p. 574], concerns theory is “a view that conceptualizes teacher’s

growth and development as a process of passing through concerns

for self (teacher) to task (teaching) to impact (pupil).” Further, these

authors describe the three stages as follows:

● Self [survival] stage. “The first stage of teaching during

which beginning teachers focus primarily on their own well-

being rather than on their learners or their process of

teaching” [4, p. 5].

● Task stage. “The second stage of teaching in which a

teacher’s concerns focus on improving his or her teaching

skills and mastering the content being taught” [4, p. 5].

● Impact stage. “The stage of teaching when instructors

begin to view their learners as individuals with individual

needs” [4, p. 6].

The educational psychology textbook from which the above de-

scription was taken is itself an example of how concerns theory has

been used as a teaching tool. The textbook introduces concerns the-

ory in the first chapter, provides a questionnaire that teachers can

use to help characterize their own concerns in terms of the theory,

and then discusses how the material in the related course relates to

those different concerns [4].

In the time since Fuller’s work, researchers have sought to con-

firm the basic propositions of the theory: the three categories and

their occurrence as a developmental progression. This additional

work has used not only open-ended data collection methods like

Fuller’s, but also various survey instruments that ask teachers to rate

the extent to which they are concerned about specific items (e.g.,

[5]). Researchers have also sought to extend the work to teachers

beyond the pre-service level to in-service teachers [6], beginning

teachers [7], teachers over their first seven years [8], teachers with

significant teaching experience and also teachers in other cultures

(e.g., more than 15 years, Lebanese teachers, [9]). Researchers have

also extended the work into the specifics of multicultural education

[10] and science education [7].

Hall and his colleagues built on Fuller’s work in their effort to

characterize how concerns evolve when teachers are in the process

of adopting innovations [11, 12]. The product of their effort is the

Concerns-Based Adoption Model (CBAM), an expansion of

Fuller’s three stages into six stages of concerns that educators can

encounter with the implementation and use of an innovation.

These stages and their alignment with Fuller’s original categories

are described in Table 1, using the words of Hall and Hord [11].

While this adoption of innovation work has been criticized for

not having more theoretical critique [13], the CBAM researchers

are unique in that they have developed an entire suite of tools for

helping instructional consultants (e.g., a stages of concern question-

naire, a stages of innovation questionnaire). Based on their experi-

ences with the model and these tools, they argue that studying

stages of concerns helps instructional consultants and administra-

tors predict and circumvent initial barriers to innovation adoption

as well as varying reactions to sub-components [11].

Over time, the research results (both the research focused on

Fuller’s ideas and the research such as CBAM that has been in-

spired by her work) have provided support for the three core cate-

gories of Self, Task, and Impact. These results suggest that future

work with concerns theory is on solid ground when using the cate-

gories as a means for organizing concerns, particularly when there is

opportunity to see what types of concerns populate the categories.

However, the results have provided less clear support for the devel-

opmental proposition that Self concerns give way to Task concerns

which give way to Impact concerns as the teacher gains experience.

Rather, researchers have noted that Self concerns may reduce over

time but do not seem to go away entirely, Task concerns are often

relatively limited in number, and Impact concerns are often the

largest category even for the most novice of teachers (e.g., [8]). This

suggests that future work not assume a strict development progres-

sion, but rather focus on documenting the relative levels of concerns

in each category and looking for explanations for why those levels of

concerns exist.

B. Bringing Concerns to Engineering EducationWhile teaching concerns have been used as both a lens for

understanding and a tool for impacting teaching at the K-12 level

(and in undergraduate teaching preparation programs generally),

we were not able to find any published accounts of the teaching

concerns of engineering educators. Thus, the opportunity exists to

document and reflect on the teaching concerns of engineering

educators. There is also reason to be cautious in assuming that these

296 Journal of Engineering Education October 2007

frameworks will let us fully account for the range of concerns we

find. On a surface level, there are clear differences between engi-

neering education and K-12 education in terms of the topics being

taught, the academic level of the students, and the role of funded

research at the heart of the Research Extensive context. Focusing

specifically on the educator in engineering education, we can note

that (a) teaching is typically not the only responsibility of engineer-

ing educators who often have significant research and service

responsibilities, (b) engineering educators may not receive formal

training for their role as educators, and (c) engineering educators

often have a great deal of autonomy in what and how they teach. As

a result, we might anticipate finding surprising topics within exist-

ing Fuller and Hall categories as well as topics that fail to be

captured by these categories. Under such circumstances, an ex-

ploratory approach has merit since it can help us discover as well as

characterize and confirm.

C. Instructional Consultations as a Context for Studying Teaching Concerns

Instructional consulting sessions are a common approach to pro-

fessional development in the higher education context, and typically

complement other approaches to faculty development such as poli-

cy setting, workshops that help educators adopt specific pedagogical

approaches, and efforts to develop new pedagogical approaches. In

an instructional consultation, the client (typically an educator) dis-

cusses one or more teaching issues with the instructional consultant,

who in turn offers suggestions and resources that concurrently ad-

dress the client’s issue and highlight effective teaching practice [14].

Because the instructional consultant is typically working togeth-

er with the client to address client issues, instructional consulting

represents a promising context for identifying a range of engineer-

ing educator concerns. Further, there are at least two reasons why

concerns that are voiced as part of the consultation process are an

excellent complement to concerns identified directly by educators in

response to surveys or prompts (the technique used in much of the

previous work on teaching concerns). First, concerns revealed in the

context of actually working on teaching situations can be considered

more situated and therefore possibly more authentic. Second, by

looking at the concerns that are revealed through the consultation

process, we do not rely solely on the educators’ relative ability to de-

scribe their teaching concerns.

Instructional consulting is also challenging as a context for

identifying engineering educator concerns for a number of reasons.

For example, instructional consulting sessions are typically private

events making it challenging to get access to the activity in the

event. Also, while instructional consultants typically focus on the

needs of their clients, they do have their own expertise which can af-

fect the direction that a consultation takes. Finally, because a con-

sultation is a two-party event in which the consultant in facilitating

the educator, this can make it difficult to determine whether the ed-

ucator had the concern prior to the consultation or if it arose during

the consultation.

D. Research Questions and General ExpectationsThe overarching question guiding this research was: What types

of engineering education teaching concerns are revealed through

the instructional consultation process? Our approach was founded

on the assumption that concerns arising in an instructional consul-

tation context are by definition linked to teaching and thus are

teaching concerns. Based on this assumption and the information

presented above, we proceeded with the following specific ques-

tions and general predictions:

● Using Fuller’s Self-Task-Impact model as a means for

categorizing types of concerns, we asked: Which concerns


Table 1. Categories of concerns used in the two models.

expressed during the instructional consultations can be

categorized as Self, Task, or Impact? What is the prevalence

of each category? What specific issues are being addressed by

concerns in each category?

● Using Hall’s notion of adoption as a specific aspect of teach-

ing and CBAM as a framework for understanding the con-

cerns associated with adoption, we asked: What is the preva-

lence of concerns related to the adoption of any type of

innovation? For those concerns related to the adoption of an

innovation, which concerns can be categorized in terms of

Hall’s Concerns-Based Adoption Model? What specific is-

sues are being addressed by the concerns in each category?

● Finally, working from the notion that these two models may

not fully or more effectively describe all of the concerns we

would collect, we asked: Are these models sufficient for orga-

nizing all of the teaching concerns of engineering educators?

What types of concerns do we see when we look to the data

using inductive thematic analysis?

Although engineering educators are not formally trained as edu-

cators, teaching is a job requirement and continued employment

suggests that they are relatively successful. As a result, we anticipat-

ed finding concerns in all three of Fuller’s categories in the consulta-

tion debriefing transcripts, but with the greatest number of con-

cerns in the Impact category due to on-the-job training and the

support of the instructional consultant. Also, because the engineer-

ing education community has devoted a great deal of effort towards

creating and publicizing teaching techniques and resources, we ex-

pected concerns related to the adoption of such techniques and re-

sources to be present. At the same time, since engineering practice

itself consists of designing new solutions to situations, we did not

anticipate adoption concerns to represent the majority of the data.

Finally, because of the differences between the prior work on teach-

ing concerns and the context of our work, as highlighted earlier, we

expected that not all of the concerns we identified would fit the as-

sumptions of these models and that an inductive analysis would be

fruitful.

III. METHOD

Our study sought to investigate the teaching concerns of engi-

neering educators, to evaluate how these concerns could be mapped

to the results of prior research on teaching concerns, and to explore

how these concerns illustrate the nature of teaching in engineering

education. In this section, we discuss how our data collection took

advantage of a unique opportunity to gain insight into teaching

concerns and how our data analysis approach reflected a commit-

ment to using systematic, auditable, and transparent techniques for

handling qualitative data.

A. Data CollectionWe collected our data by debriefing an engineering-specific in-

structional consultant (one based exclusively in a College of Engi-

neering) after 63 consultations with individual engineering educa-

tors (primarily faculty members) and teaching-related groups. This

instructional consultant worked with a wide variety of clients on a

first-come, first-serve basis and helped these clients with whatever

issues they identified. The College of Engineering and the

instructional consultant that were the focus of this study were both

known for their efforts to promote student-centered learning

practices. The transcriptions of these interviews formed the princi-

ple dataset for this study.

These debriefing interviews, which took place during 2003 and

2004, consisted of the consultant providing a narrative retelling of

the interaction with the client and then responding to a series of

open-ended questions designed to clarify and expand on points in

the narrative. This interview process represented a combination of

the formal open-ended interview and the “interview guide”

approach as discussed by Patton in his Handbook of QualitativeResearch [15]. As part of this process, the consultant was able to

report on educators’ concerns in their own language and also offer

an expert’s perspective on the issues underlying the concerns. The

exploratory nature of this project spurred the research team to

gather a large number of interviews.

The need for anonymity for the study participants presented

challenges for data collection in this study. Demographic

information, such as engineering department, gender, and level of

teaching experience could all serve to identify participants and

therefore could not be collected. As a result, we cannot report

precise information on the number of clients represented by

the data, their disciplines, or their levels of experience. This final

issue represents a point of departure from Fuller’s work in which she

could characterize her subjects in terms of their expertise

(i.e., in-service teachers, practicing teachers). Based on an approxi-

mate 20 percent repeat rate provided by the instructional consul-

tant, we estimate that our dataset represents the concerns of 40-45

different individuals.

B. Data AnalysisOur analysis of the data consisted of three activities: reducing the

data to a set of teaching concerns, deductive analysis in which we

coded these concerns using the previously identified teaching con-

cerns models, and inductive analysis in which we identified themes

specific to our data. Our overall analysis approach of combining de-

ductive and inductive activities is one of the strategies mentioned by

Patton [15, p. 452–453]. Consistent with his explanation, we chose

this approach because we wanted to see the data through an existing

theory as well as find new patterns. The purpose, approach, and

product of these activities are further elaborated below.

1) Data Reduction: Identifying Concerns: The purpose of the data

reduction was to transform the debriefing interview transcripts into

a dataset of individual teaching concerns. In our data reduction, we

focused on identifying individual concerns present in the transcripts

and then recording each concern in terms of a title, a description,

and relevant excerpts from the transcripts that represented the “evi-

dence” of the concern. Where possible, language from the transcript

was also incorporated into the concern title and description. When

identifying concerns, we focused on identifying any concerns that

appeared in the transcripts, resulting in teaching concerns beyond

those associated with the engineering educator clients.

Three members of the research team coded the transcripts for

teaching concerns. Initially, all three coders independently coded

several transcripts and then compared the results in terms of (a) the

specific concerns identified and (b) the type of evidence recorded for

the concerns. Once we were satisfied that each coder understood

the process, all remaining transcripts were coded by an individual

coder using NVivo qualitative data analysis software, and the results

for each transcript were then summarized in a Word document


which was presented to the other coders for review and discussion.

These discussions often resulted in refinement to the concern titles

and descriptions in order to better capture the essence of the con-

cern represented in the data. This coding process resulted in the

identification of 376 teaching concerns that are documented in cod-

ing summaries for each of the 63 transcripts. Example concerns, as

identified by their title and the transcript from which they originat-

ed, are given below:

● My students “seem like they don’t want to be …there.”

(Indiv_36)

● Are my ideas for the Broader Impacts section of an NSF pro-

posal any good? (Indiv_37)

● I’m alone and without professional allies in my bid for full

…professorship. (Indiv_58)

● Peer-evaluated faculty feel “put upon” and get conflicting in-

formation from reviewers. (Indiv_57)

2) Deductive Analysis: Mapping Concerns to the Theories of Fullerand Hall: The purpose of the deductive analysis was to use the

teaching concern models presented earlier to better understand the

types of concerns we had collected. In particular, we sought to de-

termine the number of concerns that fit into the categories defined

by each model and the general topics represented within each cate-

gory. Figure 1 provides an overview of our deductive analysis

process.

We started this analysis by filtering the entire dataset of concerns

relative to two assumptions underlying the previous work on teach-

ing concerns: we filtered for those concerns belonging to engineer-

ing educators, and then filtered for concerns related to the

educators’ core teaching activity (defined as some type of interaction

with students). Two coders coded the entire dataset of teaching

concerns relative to each of these filters, then met to determine the

level of agreement in each case (reported as a measure of reliability),

and finally negotiated all disagreements to consensus. The two

coders then coded the resulting subset of concerns (the engineering

educator core teaching concerns) relative to Fuller’s three categories

of Self, Task, and Impact, met to determine the level of agreement,

and negotiated all disagreements to consensus.

To code the concerns relative to Hall’s Concerns-Based Adop-

tion Model, we first filtered the engineering educator core teaching

subset for concerns specifically related to the adoption of a teaching

innovation. We used a liberal notion of innovation as any teaching

practice with norms, which is consistent with Hall’s explanation.

We then coded this subset of the concerns relative to Hall’s cate-

gories. As in the previous case, the filtering process and the coding

process were both completed by two coders who first coded inde-

pendently and then met to determine the level of agreement and to

negotiate disagreements to consensus. In the Results section, we re-

port on the reliability of each coding step, the number of concerns

that ultimately fell into each category, and the nature of the con-

cerns that fell into the categories.

3) Inductive Analysis: Identifying Emergent Themes: The purpose

of the inductive analysis was to identify patterns in the concerns that

had not been captured by the deductive analysis. Our overall ap-

proach consisted of identifying themes, confirming the extent to

which the themes were present in the dataset, and then looking for

patterns in the themes. To identify the themes, we used a “data


Figure 1. Overview of the deductive coding process.

wall” affinity process—we created a physical environment

(the “wall”) in which we could view all concerns concurrently and

thus immerse ourselves in the data [16, 17]. Using this technique,

three coders visually scanned the 376 individual concerns based on

their title and description and documented themes that were pre-

sent. For example, the concern “My students seem like they don’t

want to be there” was one of the concerns that were clustered

around the theme “Educators questioning how much responsibility

they should take for student learning.”

We used a member check procedure as a means to further vali-

date the themes [18]. Stakeholders in the member check reviewed

the results for relevance and comprehensiveness. Our member

check consisted of sharing the themes with a panel of engineering

education experts who were asked to comment on those themes

that were most familiar and those that they had encountered most

often in their interactions with engineering educators. This infor-

mation influenced our decision concerning which three themes to

present in the Results section of the paper.

IV. RESULTS

Our process of data collection permitted us to identify 376 con-

cerns. These concerns represented a broad set of issues ranging from

relatively specific concerns such as how to address disruptive students,

to such broad concerns such as how to create a culture that values

teaching and how to write better grant proposals. Furthermore, the

concerns we identified belonged to a range of stakeholders including

engineering educators, students, the instructional consultant, deans,

chairs, and the National Science Foundation. The analysis of these

376 concerns is presented in the subsequent sections.

A. Deductive Analysis: Interpreting Data via Existing Teaching Concern Models

As explained in the Method section, in order to code the con-

cerns using the two teaching concerns models, we first had to filter

the entire dataset for those concerns fitting the assumptions of the

models (concerns belonging to educators and related to the educa-

tors’ core teaching activities). The first level of filtering, identifying

the concerns belonging to engineering educators (see Figure 1), was

completed with 88 percent agreement and reduced the dataset from

376 concerns to 180 concerns. The 196 concerns that were filtered

out included the concerns of the instructional consultant, adminis-

trators, funding agencies such as the National Science Foundation,

and even concerns belonging to students. The second level of filter-

ing, identifying the core teaching concerns (see Figure 1), was com-

pleted with 79 percent agreement and reduced the data from 180

concerns to 120 concerns. The 60 concerns that were filtered out

included concerns about the instructional consultation process and

concerns related to grant writing. The remaining 120 concerns rep-

resented the concerns that were consistent with the two teaching

concern models.

1) Concerns Interpreted Through Fuller’s Self-Task-Impact Model:In coding the 120 concerns that were identified as belonging to en-

gineering educators and related to their core teaching activities, we

identified 31 Self concerns, 19 Task concerns, and 70 Impact con-

cerns. This coding was completed with a reliability of 81 percent as

measured through agreement. Table 2 provides an overview of the

results of this coding.

Within the 31 Self concerns, some trends emerged. For exam-

ple, several of the concerns related to negative repercussions of

teaching activities, with several educators voicing concerns about

credibility (such as a concern about women’s attire having a negative

impact on respect and credibility), reputation (such as not wanting

to be “labeled a radical” for expressing one’s views), departmental

standing, and also being blamed for poor teaching evaluations. An-

other thread within the Self concerns related to concerns about dis-

comfort and/or vulnerability, such as being personally put on the

spot and feeling uncomfortable outside one’s area of expertise. A

third thread within the Self concerns was the general issue of diffi-

culty and workload, such as concerns about the difficulty of imple-

menting active learning.

The 19 Task concerns made it the least populated category. To

be coded in this category, concerns needed to focus on general “how

to” issues. Two types of concerns that did end up falling into this

category were concerns about (a) approaches and opportunities to

improve one’s teaching skills and (b) curricular level activities such

as gaining feedback about possible curricular choices, making cur-

riculum changes, and figuring out one’s autonomy to adopt and

adapt curricular materials. Inspection of the results suggests that the

low number of Task concerns resulted not from a lack of “how to”

concerns but rather from the fact that many such concerns went be-

yond the simple “how to” to the realm of “how to in the best interest

of a student,” which resulted in the concern being coded as an Im-

pact concern.

With 70 concerns, the Impact category was the most prevalent.

These concerns covered a wide territory in terms of teaching activi-

ty, including issues of:

● maintaining quality while providing accommodation,

● keeping the curriculum up to date to better prepare students

for industry,

● improving students’ engagement with their own learning,

● inclusiveness in terms of including all kinds of students.

Impact concerns also varied in terms of the number of students

involved, how the concerns were framed, and their relationship to a

disciplinary topic within engineering. For example, while some

concerns focused on issues related to a single specific student


Table 2. Results of the deductive analysis.

(e.g., dealing with this disruptive student), other concerns focused

on relationships with students at the individual level (e.g., mentor-

ing issues), groups of students within a class (e.g., dealing with the

students who do not want to be there), groups of students within

engineering (e.g., underrepresented students), and all students.

Also, while some concerns were framed as problems (e.g., dealing

with a disruptive student), other concerns were framed as goals

(e.g., maintaining quality while providing accommodation). Final-

ly, while some concerns were tightly tied to a topic being taught by

an instructor (e.g., concerns about supporting student exam prepa-

ration, concerns about how to link content to the engineering con-

text, and concerns about teaching engineering principles before ap-

plication examples), other concerns were related to engineering in

general but not to a class (e.g., concerns about engineering students

being trained to be passive, concerns that engineering students have

skewed perceptions of engineering as a discipline) and even to issues

not very specific to engineering (e.g., a concern that male educators

need to learn to advise female students).

2) Concerns Interpreted Through Hall’s Concerns-Based AdoptionModel: Of the 120 educator core teaching concerns, we identified

66 as related to adoption of innovation (reliability of 77 percent as

measured by agreement). The range of “innovations” reflected in

these concerns included:

● strategies and practices that form a part of teaching, such as

using textbooks and disability accommodation,

● broader pedagogies for classroom teaching, such as service

learning, group work, and active learning,

● practices such as mentoring and advising that have teaching

relevance but typically occur outside of the classroom,

● assessment and monitoring practices, such as student ratings,

that are used to collect information and determine how well

other strategies are working, and

● various practices such as information discussion groups that

educators use to learn about and improve their teaching

skills, and reflect on the other practices mentioned.

While some of these innovations seem rather loosely defined,

what was common about them in the context of the concerns is that

they were treated as an existing practice that could be learned about

and had norms.

We were able to analyze these 66 adoption of innovation con-

cerns with an agreement of 87 percent. The results of the analysis of

these 66 adoption of innovation concerns relative to Hall’s CBAM

model are reported in Table 2.

As indicated in Table 2, we found Consequence to be the most

prominent category (which is not surprising since Impact was the

prominent category in the previous coding). These 29 Consequence

concerns represented issues such as (a) understanding how to use

the innovation with students and (b) determining what mediates an

effective use of the innovation. We also noted one concern explicitly

capturing tradeoffs associated with the innovation (i.e., a concern

about how to dock late assignments without violating student

rights).

While we did not identify any Awareness or Refocusing

concerns and only identified one Informational concern and one

Collaboration concern, we did find a number of Personal concerns

(n � 21) and Management concerns (n � 12). The Personal

concerns reflected links between using the innovation and (a) career

issues such as promotion and tenure, (b) self image and work image,

(c) workload, and (d) managing perceptions of one’s expertise. The

Management concerns reflected issues related to (a) the level of

freedom and flexibility inherent in using the innovation, (b) chal-

lenges inherent in using the innovation, (c) identification of tasks

associated with the innovation that were not student specific, and

(d) the types of resources beyond student capabilities necessary to

use the innovation.

Collectively, this section has focused on analyzing the concerns

of our engineering educators relative to existing models. We were

able to analyze 120 of our concerns using the models. The remain-

ing concerns were either concerns of educators that were not related

to their core teaching responsibilities and/or concerns of engineer-

ing education stakeholders other than the educators. In the next

section, we turn to the inductive analysis which, while prioritizing

the core teaching concerns of the engineering educators, also sought

to bring these other concerns back into the analysis.

B. Inductive Analysis: Seeking Themes Across an Entire Set of Concerns

The themes which emerged from the affinity process illustrate

the complexity of engineering education in a research-focused

environment. Table 3 presents these 14 themes, organized

alphabetically.

Due to space limitations, we cannot go into depth on each of

these themes. As a result, in the remainder of this section, we focus

on presenting three of these themes in greater detail. These themes

were chosen not only because of the richness of the data relative to

the theme but also because of their ability to highlight the breadth

of our dataset in terms of concerns that were consistent with the as-

sumptions of the Fuller and Hall models, and also concerns that

went beyond the assumptions of those models (e.g., educator activi-

ties beyond core teaching, concerns of stakeholders other than edu-

cators).

In this vein, the first theme, “Educators questioning how much

responsibility they should take for student learning,” was chosen be-

cause it clearly represents a core teaching concern of the engineering

educators in this study. The second theme, “Educators grappling

with many roles beyond classroom instructor,” was chosen because

it captures the complexity of engineering educators’ professional

lives, a complexity that goes beyond the vision of teaching that

Fuller describes. The third, “Educators, administrators, and fund-

ing agencies trying to create a culture that values teaching,” was

chosen because it is a theme that focuses beyond core teaching ac-

tivities and also illustrates a shared effort by the many stakeholders

in engineering education.

1) Educators Questioning How Much Responsibility They ShouldTake for Student Learning: Engineering educators may have diffi-

culty determining how much responsibility they can take for their

students’ learning. While being actively engaged in supporting their

students, participants in this study expressed a number of concerns

related to the degree to which students engaged in course activities,

students’ preparation for the higher education setting, and some ed-

ucators’ perceptions that students put less time and energy into their

coursework than the educators do themselves. Given that engineer-

ing educators are increasingly being required to change their teach-

ing to increase student learning, this apparent discrepancy between

student engagement and expected learning leaves educators in an

ambiguous position. Each of the following sub-themes describes a

particular aspect of educators questioning how much responsibility

they can take for student learning.



Table 3. Results of the inductive analysis.

a) Educators questioning students’ engagement with their ownlearning process: Engineering educators may be concerned about

how their students approach their own learning. Participants in this

study expressed concerns about a variety of student behaviors that

could be indicative of a lack of engagement in their own learning.

One educator spoke about “a significant amount of students skip-

ping class” while another suggested that his students “seemed like

they didn’t want to be there.”

Moreover, the educators were concerned that they themselves

would be blamed for poor student performance. One educator had

designed a course that included students taking online “pre-flight

quizzes” before class time, a non-graded activity that was intended

to reinforce student learning and to help the instructor prepare for

that day’s class session. The client reported that a number of stu-

dents were skipping class and that 20 percent of the class was not

taking the quizzes:

The client was concerned that his students would blame

him for their poor performance. Why would they blame

him? Would they see material covered in lecture and think

“you gave me the impression the online material covered the

lecture?” Would they just blame him in general for not

teaching well? (Indiv_69, Lines 182–185)

Several educators expressed concerns about the relative work-

loads that educators and students bear in preparing for class. One

such concern questioned the degree to which students came pre-

pared for class, especially regarding the reading. The instructional

consultant responded to her client’s concerns as follows:

So we talked about how in a traditional class the students

don’t do a lot of work while the instructor does a lot of prep.

But in an interactive course, where [students are] actually

doing some assignments ahead of time.…the students are

much more active in the class because they’re prepared to

talk.… (Indiv_28, lines 200–204)

This subtheme describes one aspect of educators’ uncertainty

about the degree to which they can be held responsible for student

learning: the perception that some students may be taking less than

adequate responsibility for their own learning process. As the fol-

lowing subtheme describes, educators also realize that students may

be lacking some of the baseline skills for functioning well in the

higher education setting.

b) Educators realize that students have difficulty in the higher educa-tion setting: Another factor limiting how much responsibility educa-

tors can take for student learning is students’ preparedness for the

higher education setting. Educators in this study expressed concerns

about students’ ability to perform the basic tasks needed to learn at

the university level. One educator, for example, suggested that stu-

dents may lack the ability to effectively work with a textbook:

The client had a hypothesis about student engagement and

use of the textbook. Students don’t know how to read a

textbook.…They really don’t know how to get information

from a textbook (Indiv_24, lines 25–28).

Educators also expressed concerns about a variety of possible

causes for poor student performance. One educator was concerned

about how well a student’s undergraduate math education prepared

her for graduate-level engineering courses. Another educator ex-

pressed concern about some students’ lack of time management

skills, suggesting that students lack “realistic expectations” about the

number of hours required to effectively complete course-related

responsibilities.

There was also a perception that the higher education setting it-

self was not supporting student learning. The instructional consul-

tant referred to one author’s framing of this institutional bias:

She said the environment is hostile toward helping students

achieve a degree and is geared more towards weeding out

those who are struggling. They need to have a less

competitive environment (Indiv_28, lines 45–48).

The educators were also aware that some students lacked a posi-

tive self-image in regard to their own scholarship. This seemed par-

ticularly true for female graduate students in engineering:

The client and I had [a number of conversations] about

women grad students.…that they run into these kinds of

things more often. They convince themselves that they’re

stupid…even though they know analytically that they are

not (Indiv_30, lines 79–82).

While the first subtheme primarily addressed student behavior

and abilities, this second subtheme captures institutional deterrents

to student learning, whether those deterrents are a lack of adequate

preparation or the perception of higher education as a hostile envi-

ronment. These two subthemes capture educator concerns about

students’ ability to engage the higher education setting as a learning

environment. In the face of these concerns, educators are also at-

tempting to create a positive learning experience for their students,

as the next subtheme attests.

c) Educators want students to excel: In the midst of these concerns

about students’ ability to engage their own learning, some educators

in this study also expressed concerns about creating a classroom en-

vironment that best supports learning. These concerns ranged from

questions about specific teaching techniques to more general ap-

proaches to teaching:

The client writes: I’m teaching a new course and I’ve never

taught it before. I usually just figure it out the first year and

try new things. But I hate to do that to the students. So if

you have any ideas on how to make it not so hard on the

students, I’d really like to know (Indiv_67, lines 7–9).

Some educators in this study approached the goal of increased

learning by learning to build better rapport with their students and

create an open atmosphere for discussion in the classroom. Others

sought to make the structure of the course and their own teaching

more transparent.

Overall, this theme captured an ambiguity in teaching: educators

wanting students to excel while also recognizing that some students

do not or cannot engage the learning process sufficiently to reach

the expected level of competency. While this paradox is not new,

educators may feel caught between actual student performance and

the expectations of administrators and funding agencies for

increased student learning. As a result, such educators may benefit


from a community-wide discussion of how much responsibility

they can take for student learning in classroom context and how

much responsibility students must bear. At the same time, class-

room instruction is but one of a number of responsibilities that en-

gineering educators face on a daily basis. The following theme

addresses the complexity of educators’ professional lives, specifically

those of faculty, by recording some of the many roles they perform

within and beyond that of classroom instructor.

2) Faculty Grappling with Many Roles Beyond ClassroomInstructor: Fuller’s Self-Task-Impact model of teaching concerns,

which was founded in the study of undergraduate student teachers

and K-12 teachers, focused primarily on educators’ responsibilities

as classroom instructors. While the engineering educators repre-

sented in this study also had a strong focus on the classroom and

were actively engaged in improving student learning, these educa-

tors’ concerns revealed that they were also engaged in activities asso-

ciated with a variety of other roles. For example, the concerns

revealed roles including employee, department member, domain

expert, grant writer, industry liaison, mentor, policy-maker, and

researcher. Given this multiplicity of roles, which are often them-

selves in a state of flux, engineering educators in this study used the

instructional consultation process to address challenges beyond

those usually associated with classroom instruction. The following

sections discuss a sample of the roles that were revealed. They are

arranged by their relationship to the classroom, from those that are

directly associated with classroom instruction to those that involve

the greater academic environment.

a) Multicultural Educator: Educators at all levels are increasingly

expected to incorporate multicultural teaching methods into their

teaching practices [10]. Yet engineering educators may have

difficulties implementing diversity-based instruction. Some engi-

neering educators represented in this study had limited understand-

ing of general pedagogical terminology and therefore needed to

have multicultural education materials “translated” for them. The

instructional consultant also suggested that some educators may

understand the importance of multicultural education but may not

recognize that there is a problem in their own classrooms. In this

study, the instructional consultant actively supported engineering

educators in improving their multicultural education skills.

b) Industry liaison: Several engineering educators represented in

this study sought assistance from the instructional consultant to

better incorporate common issues and practices found in industry.

For example, one educator wanted to take a wide perspective of “in-

troducing the discipline and its dynamism” to students and giving

them a realistic perspective on his rapidly changing field. Another

educator approached the instructional consultant for assistance at a

finer grain, incorporating “real world” examples into the curriculum

as a way to increase relevance for students while also preparing them

for employment.

c) Researcher: One defining difference between Fuller’s partici-

pants and the educators represented in this study is the professional

requirement to conduct funded research. Engineering educators

represented in this study used the instructional consultation setting

to express concerns about research demands and the interplay of

teaching and research. For example, one educator was concerned

that teaching and research seemed like two separate activities and

sought a better understanding about how to integrate them. Anoth-

er educator was concerned about how his research approach could

affect the tenure and promotion process.

d) Grant writer: Engineering educators in this study also came to

the instructional consultation process seeking help on writing grant

proposals, the necessary first step in the acquisition of funded re-

search. Many of these educators sought specific guidance on writing

the Broader Impacts section of an NSF proposal. They asked for

help on writing about the educational aspects of the proposed re-

search, asking especially for appropriate supporting citations. Oth-

ers wanted more global feedback on the quality and acceptability of

the proposal as a whole. In relationship to this and the preceding

Researcher role, it is interesting to reflect on how these educators

came to use instructional consultation to support their research-

related responsibilities.

e) Department member: Engineering faculty belonging to a de-

partment represents a significant aspect of their work context. Some

educators represented in this study expressed concerns about how to

cope with challenging communication patterns within their depart-

ments. For example, an international faculty member worked with

the instructional consultant to better understand how to interpret

the social dynamics within his department. New educators ex-

pressed concerns about the tenure and promotion process, ques-

tioning the impact of their student ratings or their research projects

on their advancement towards tenure. Women educators also ap-

proached the instructional consultant for support in working in a

traditionally male academic department. For all of these educators,

the instructional consultant seemed to serve as an interpreter of the

academic culture itself. While this range of roles may not be surprising, the fact that

these roles were all invoked during instructional consultation

sessions reflects the intricate way that teaching permeates faculty

life. In the next section, we turn to a theme that reflects not only

the concerns of the engineering educators that have been reflect-

ed in this section and the previous section, but also concerns as-

sociated with other stakeholders in the engineering education

system. The final theme discussed in this paper addresses how

the engineering education community is creating a culture that

supports teaching.

3) Educators, Administrators, and Funding Agencies Trying toCreate a Culture That Values Teaching: Several of the concerns in

our dataset suggest an underlying desire for and efforts to create a

culture that values teaching. For example, some educators ex-

pressed a desire for a forum to discuss teaching issues within their

departments and actively sought out assistance with various as-

pects of their teaching. More broadly, administrators and stake-

holders such as funding agencies also wanted to build a culture

that values teaching by seeking ways to motivate individual educa-

tors to adopt new methods, to spread teaching innovation beyond

innovators, and on an even more fundamental level, to get

educators’ buy-in for pedagogical change. The articulation of

these issues provides insights on the barriers that educators

and other stakeholders encounter when trying to create such a

culture.

a) Wanting a culture that values teaching: Educators represented

in this study, as well as the instructional consultant, expressed a de-

sire for a culture that values teaching and teaching innovation. In

particular, these educators wanted explicit discussions of teaching to

be an ongoing aspect of academic engineering culture, whether sup-

ported at the college, the department or program levels, or simply

among their peers. In one consultation, an educator/administrator

pointed out a perceived need for a greater discussion of innovative


teaching techniques:

There isn’t a forum for people to talk about [teaching]. And

this faculty member realized that. He said that it is not

working to have the innovators talking to each other in a

committee meeting (Indiv_1, lines 123–126).

While the preceding excerpt captures an interchange between

the instructional consultant and an academic administrator, engi-

neering educators themselves also recognized the importance of

creating opportunities for educators to come together and help each

other improve their teaching. For example, one educator e-mailed

the instructional consultant to schedule a consultation with the fol-

lowing observation:

I thought it might be a good idea to have a lunch workshop

where an expert on engineering teaching can do a workshop,

very similar to the one… where Rich Felder spoke on ‘Why

Should I Change the Way I Teach?’ … I think it would be a

great opportunity to really use this time to infuse into the

community the importance of active/experiential learning

and how easy it is to implement this (Indiv_60, lines 15–24).

For the engineering educators in this study, instructional consul-

tations served as a forum to talk about their own teaching. The

availability of instructional consulting represents one element of a

culture that values teaching.

b) Motivating educators as a key to creating the culture: When engi-

neering educators and other stakeholders are working to increase

the visibility and value of teaching, they can be challenged by those

educators who appear on the surface to be “recalcitrant” or some-

how lacking in motivation. For example, a department chair

worked with the instructional consultant to increase awareness of

teaching in his department, especially among established faculty:

We were talking about faculty buy-in, which we talk about

every time because this is a big concern of his. He’s thinking

perhaps about the more negative end of the distribution of

faculty and thinking how he’s going to reach [them]

(Indiv_73, an lines 329–333).

Another educator, who was writing a proposal for a department-

wide pedagogical change, wanted to increase the awareness of

teaching among his peers. He sought help in framing his efforts in a

way that would appeal to the broadest set of educators:

He talked about his idea of how do you find out what

they’re even interested in when it comes to teaching? We

talked a lot about faculty buy-in, that if you’re going to talk

about pedagogical change, faculty have to have a reason to

do it. They have to be able to take ownership of it

(Indiv_43, lines 93–96).

Finally, one educator suggested that the bottom line may be the

best way to motivate certain kinds of faculty to increase their

teaching skills:

And I said well actually there’s a lot of proof that [active

learning] works…and he said yeah but it needs to impact

student ratings because that’s what they look at in the tenure

and promotion process. That’s the reward structure you

know (Indiv_7, lines 149-152).

Larger scale attempts to motivate educators to change their

teaching were also reflected in the concerns related to this theme.

For example, funding agencies such as the NSF are actively working

to create a culture that values teaching through initiatives that in-

clude the funding of research on engineering education and the op-

portunity to satisfy the broader impacts requirement by linking the

research to educational activity.

V. DISCUSSION

In this paper, we have reported on a study of teaching concerns

arising in one engineering education context—consultations

between engineering educators and an instructional consultant. We

collected narrative accounts of 63 consultations between the in-

structional consultant and engineering educators (a place where we

expected concerns to be voiced) and analyzed these accounts to cre-

ate a dataset of 376 individual concerns.

In our deductive analysis of the concerns relative to Fuller’s Self-

Task-Impact model, we first found that only 120 of our concerns fit

the assumptions of the model in that these were concerns of educa-

tors related to their core teaching responsibilities. The concerns be-

yond this 120 subset represented either concerns of engineering edu-

cators beyond their core teaching responsibilities (e.g., grant writing)

and/or concerns belonging to stakeholders in the engineering educa-

tion process other then the educators themselves (e.g., instructional

consultants’ concerns about how to best market themselves to engi-

neering educators). Our analysis of the 120 core teaching concerns

found the majority of the concerns to be in the Impact category,

showing the many ways that the engineering educators were endeav-

oring to take into account student issues. We also found concerns in

two other categories of Self and Task. Of particular interest were the

many Self concerns related to the potential negative consequences of

teaching activities. Because Hall’s Concerns-Based Adoption

Model was built on Fuller’s model, we used these 120 concerns as

the beginning point for our analysis relative to CBAM. We found

that 66 of these 120 concerns fit the assumptions of the CBAM

model in that the concerns involved some form of adoption of inno-

vation. We further noted that the nature of the innovations varied

(e.g., strategies such as using textbooks, specific pedagogies such as

active learning, and more general practices such as accommodating

students with disabilities). When coding these concerns relative to

Hall’s categories, we found the majority of the concerns to be in the

Consequence category but also a significant number of concerns in

the Personal and Management categories. Collectively, these results

were consistent with our predictions.

Our inductive analysis permitted us to go beyond the limitations

imposed by the previous theories and resulted in the identification

of 14 themes that varied in the immediacy of their connection to

students. In addition to providing a brief snapshot of each of these

themes, we then reviewed three of these themes in greater detail:

the issue of how much responsibility an instructor can take for stu-

dent learning, the challenge of the many roles of an engineering ed-

ucator and the links of these roles to the teaching mission, and the

goal of creating a culture that values teaching.


A. Significance of the ResultsCollectively, these results represent a benchmark concerning the

needs of engineering educators and a basis for conversation. Al-

though the concerns represented in this work reflect a large number

of engineering educators the results in many ways are best described

as a case study of the concerns of engineering educators at one pub-

lic Research Extensive institution that arose when educators were

grappling with some issues in a supportive context. As a result, fu-

ture research is needed to know if the results are specific to educa-

tors who seek out advice, representative only of educator needs that

cannot be addressed by other resources (e.g., online tools, work-

shops), specific to this one institution, or even unique to engineer-

ing. Further, future research would help clarify if engineering edu-

cators have the same types of concerns when they are on their own.

The exploration of these issues can clearly be a part of the conversa-

tion stimulated by the work.

These results also suggest that the engineering educators in this

study deserve merit for the extent to which they were functioning in

a learner-centered way. Current best practice guidelines for educa-

tion highlight the importance of good instruction being “learner-

centered” (e.g., [19]). We believe that many of our results represent

evidence of learner-centered practices and illustrate the various ways

that learner-centered thinking can manifest in engineering educa-

tion. For example, the number and nature of the Impact concerns in

the Fuller analysis and the number and nature of the Consequence

concerns in the Hall analysis brought to the forefront the extent to

which the engineering educators were grappling with student is-

sues. Also, the theme of how much responsibility to take for student

learning provides a more in-depth look across the participants at

one specific student-centered concern of engineering educators.

The other two themes that we explored were not specifically about

being student-centered on the surface, but were nonetheless clearly

tied to students. For example, the “creating a culture” theme, in its

immediate form, focuses on the educator but a broader view of this

theme suggests that a culture that values teaching would provide a

space in which educators can focus on being student-centered.

Also, the “many roles” theme points to the different contexts for

being student-centered. Finally, even the Self concerns, which on

the surface can be seen as evidence of teacher-centeredness, can be

linked to learner-centeredness when viewed as challenges or obsta-

cles to being learner-centered. For example, the Self concerns relat-

ed to issues of negative repercussions can certainly be thought of as

obstacles, or even the source of resistance to practices that may be

more learner-centered.

The results also prompt thought in terms of productive ways to

conceptualize or describe teaching, which has added significance

given that the underlying framing of an activity such as teaching can

significantly affect how we support that activity. In a nutshell, the

results point to adoption of innovation and professional problem-

solving as promising ways to conceptualize the activity of engineer-

ing educators. In our study, we found over half of the core teaching

concerns to be related to adoption of some type of innovation. The

results also complicate the issue of adoption in that the majority of

the concerns related to adoption were Consequence concerns gen-

erally addressing how to adopt or adapt the “innovation” to the par-

ticulars of a situation while maintaining quality for students.

The processes and decisions associated with adoption can be

viewed as just one aspect of the other lens we believe the results sug-

gest as productive—the notion of professional problem-solving as

characterized by Schon [20]. In his work on the nature of activity in

the professions, Schon contrasted the models of technical rationali-

ty and professional problem-solving. In a technical rationality view,

the professional learns the techniques of the profession and applies

these techniques to the well-formed problems of professional prac-

tice. In our dataset, such a vision might have shown up as a large

number of concerns in Fuller’s Task category and Hall’s Manage-

ment category suggesting educators’ grappling with simply under-

standing the techniques of the profession (i.e., teaching). Rather,

we saw a large number of Impact concerns, specifically concerns

often related to adopting an innovation to the particulars of a situa-

tion and developing solutions to specific problems of practice. Fur-

ther, two of the three themes included in this paper can be charac-

terized as examples of the complicated problems of practice (how

much responsibility for teaching and creating a culture that values

teaching). The “creating a culture” theme can also be characterized

as the problem of creating conditions suitable for educators to en-

gage in this problem-solving. The third theme (many roles of engi-

neering faculty) can be seen as describing factors that complicate the

problems of practice. These results seem highly consistent with

Schon’s characterization of professional problem-solving, suggest-

ing that the engineering education community might reflect on the

extent to which such a problem-solving view is reflected in the sup-

port provided for engineering educators.

One final note is the implication of the results for future efforts

to model teaching activity. Inspired in a broad sense by a desire to

understand how teaching happens in engineering education and

how we might help educators teach more effectively, we collected

data in the form of teaching concerns. Yet, analyzing the data rela-

tive to existing teaching concern models only let us account for less

than half of our data (the portion representing the “sharp end” of

teaching, educators interacting directly with students). In this

paper, we used inductive analysis to bring in the rest of the data (the

“blunt end” of teaching, educators focused on non-core teaching ac-

tivities and other stakeholders). The presence of so much data that

could not be analyzed through the models we identified suggests a

need to look for other models. In particular, a desirable model

would be one that can help to organize teaching-related issues be-

yond those associated with direct interaction with students, repre-

sent a wide range of stakeholders beyond those educators who have

immediate interaction with students, and showcase how all of the

issues come together to affect how our students get taught. We be-

lieve this suggests that future research on teaching in engineering

education consider not only the adoption of innovation and profes-

sional problem-solving models identified earlier as ways to concep-

tualize teaching activity, but also consider distributed cognition

models or models from the field of complexity science as ways to

model how teaching happens across people and time.

VI. CONCLUSION

This paper focused on a study of the teaching concerns of

engineering educators as one means of exploring the needs of engi-

neering educators. The design is best described as a case study of the

concerns arising in one teaching support context (instructional con-

sultations) at one specific university (a public, research extensive

institution). The results showcase some ways in which educators are

succeeding in being student-centered and provide insight into two


productive frameworks for thinking about teaching (adoption of in-

novation and problem-solving.) The results can also inform future

efforts to investigate teaching in engineering education. In terms of

contributions, these results represent a benchmark which can serve

as a reference for future work and a basis for conversation. The

study also represents an effort to bring theories of K-12 teaching

development into the engineering education arena and showcases a

technique for exploring the concerns of engineering educators that

takes advantage of unique opportunity for collecting data.

The results suggest two considerations for ideas to support edu-

cators’ efforts to advance their teaching: provide a safe place to ad-

dress Self concerns and provide an environment to permit educators

to grapple with problem-solving concerns. Further, the results im-

plicitly showcase instructional consulting as a faculty development

strategy that meets these requirements. More generally, the results

also provide information that can be used to operationalize the gen-

eral desire for a culture that values teaching. Elsewhere in our work,

we have used the content of the educators’ concerns and insights into

the instructional consulting process to develop NEXT (Narratives to

support EXcellent Teaching), a web-support tool that lets educators

navigate to potentially relevant resources via narratives about prob-

lems faced by fictionalized educators [21, 22]. We look forward to

seeing other complimentary efforts to help engineering educators

constructively address their concerns and advance their teaching.

ACKNOWLEDGMENTS

This work has been funded by the National Science Foundation,

through “The Teaching Challenges of Engineering Faculty” grant

(EEP-0211774). Any opinions, findings and conclusions, or rec-

ommendations expressed in this material are those of the authors

and do not necessarily reflect the views of the National Science

Foundation.

The authors wish to thank the following people for lending their

expertise to this research in terms of design, analysis, and

interpretation: Robin Adams, Susan Ambrose, Cindy Atman, Jim

Borgford-Parnell, Rebecca Brent, Rich Felder, and Wayne Jacob-

son. We would also like to thank Zhiwei Guan, Yi-Min Huang,

Steve Lappenbusch, Ken Yasuhara, and Jessica Yellin for their

contributions to this paper. We also wish to thank the anonymous

reviewers for their comments and feedback on the original version

of this manuscript.

REFERENCES

[1] Brent, R., R. Felder, D. Hirt, D. Switzer, and S. Holzer, “A Model

Program for Promoting Effective Teaching in Colleges of Engineering,”

(Web) Proceedings, 1999 American Society for Engineering Education Annual

Conference, http://www.asee.org/conferences.

[2] Van den Berg, R., and A. Ros, “The Permanent Importance of the

Subjective Reality of Teachers during Educational Innovation: A Con-

cerns-Based Approach,” American Educational Research Journal, Vol. 36,

1999, pp. 879–906.

[3] Fuller, F., “Concerns of Teachers: A Developmental Conceptual-

ization,” American Educational Research Journal, Vol. 6, 1969, pp. 207–226.

[4] Borich, G.D. and M.L. Tomari, Educational Psychology: A

Contemporary Approach, 2nd ed., New York, NY: Longman, 1997.

[5] George, A.A., Measuring Self, Task, and Impact Concerns: A Manual

for Use of the Teacher Concerns Questionnaire, Austin, TX: University of

Texas, 1978.

[6] Reeves, C.K., and R. Kazelskis, “Concerns of Preservice and

Inservice Teachers,” Journal of Educational Research, Vol. 78, 1985,

pp. 267–271.

[7] Adams, P., and G. Krockover, “Concerns and Perceptions of

Beginning Secondary Science and Mathematics Teachers,” Science

Education, Vol. 81, No. 1, 1997, pp. 29–50.

[8] Pigge, F., and R. Marso, “A Seven Year Longitudinal Multi-Factor

Assessment of Teaching Concerns Development Through Preparation

and Early Years of Teaching,” Teaching and Teacher Education, Vol. 13, No.

2, 1997, pp. 225–235.

[9] Ghaith, G., and K. Shaaban, “The Relationship Between Percep-

tions of Teaching Concerns, Teacher Efficacy, and Selected Teacher

Characteristics,” Teaching and Teacher Education, Vol. 15, 1999, pp.

487–496.

[10] Marshall, P., “Multicultural Teaching Concerns: New Dimen-

sions in the Area of Teacher Concerns Research?,” The Journal of Educa-

tional Research, Vol. 89, 1996, pp. 371–379.

[11] Hall, G., and S. Hord, Change in Schools, Albany, NY: State

University of New York Press, 1987.

[12] Bailey, D., and S. Palsha, “Qualities of the Stages of Concern

Questionnaire and Implications for Educational Innovation,” Journal of

Educational Research, Vol. 85, No. 4, 1992, pp. 226–232.

[13] Anderson, S., “Understanding Teacher Change: Revisiting the

Concerns-Based Adoption Model,” Curriculum Inquiry, Vol. 27, No. 3,

1997, pp. 331–365.

[14] Turns, J., M. Eliot, and A. Linse, “Exploring the Teaching Chal-

lenges of Engineering Faculty: What Do They Really Want to Know?,”

(Web) Proceedings, 2003 American Society for Engineering Education Annual

Conference and Exposition, http://www.asee.org/conferences.

[15] Patton, M.Q., Qualitative Research and Evaluation Methods, 3rd

ed., Thousand Oaks, CA: Sage Publications, 2002.

[16] Ryan, G., and H. Bernard, “Techniques to Identify Themes,”

Field Methods, Vol. 15, No. 1, 2003, pp. 85–109.

[17] Beyer, H., and K. Holtzblatt, Contextual Design: Defining Cus-

tomer-Centered Systems, San Francisco, CA: Morgan Kaufmann, 1998.

[18] Lincoln, Y., and E. Guba, Naturalistic Inquiry, Newbury Park,

CA: Sage Publications, 1985.

[19] Bransford, J., A. Brown, and R. Cocking, How People Learn:

Brain, Mind, Experience, and School, Washington, DC: National Academy

Press, 1999.

[20] Schon, D., The Reflective Practitioner: How Professionals Think in

Action, Boston, MA: Basic Books, 1983.

[21] Eliot, M., R. Neal, and J. Turns, “Empirically Derived Design

Principles for Engineering Educator Resources,” (Web) Proceedings, 2006

American Society for Engineering Education Annual Conference and Exposi-

tion, http://www.asee.org/conferences.

[22] “NEXT: Narratives supporting EXcellent Teaching,”

http://depts.washington.edu/next.

AUTHORS’ BIOGRAPHIES

Dr. Jennifer Turns is an associate professor in the Technical

Communication department within the College of Engineering at

the University of Washington. Her research interests include engi-

neering education, user-centered design, information design,


audience analysis, and the role of technology in learning. She earned

her Ph.D. from the Georgia Institute of Technology.

Address: 245 Engineering Annex, Box 352195, Technical

Communication, University of Washington, Seattle, WA, 98195-

2195; telephone: (+1) 206.221.3650; fax: (�1) 206.221.3161;

e-mail: [email protected].

Matt Eliot is a doctoral candidate in the Technical Communi-

cation department of the University of Washington. His interests

include product design, the structure of meaningful experiences,

user-centered design, and accessibility issues.

Address: Box 352195, Technical Communication, University of

Washington, Seattle, WA, 98195-2195; e-mail: [email protected]

ington.edu.

Roxane Neal is a user researcher in Seattle’s software industry,

currently working at Microsoft. In 2006, she earned her Masters

degree from the Technical Communication department at the Uni-

versity of Washington. After graduation, she led the development

of the NEXT web site, a tool that was developed based on findings

from this work.

Address: Box 352195, Technical Communication, University of

Washington, Seattle, WA, 98195-2195; e-mail: roxane.neal@

mindspring.com.

Angela Linse is executive director of the Schreyer Institute for

Teaching Excellence and associate dean at the Pennsylvania State

University. She holds B.A., M.A., and Ph.D. degrees in Anthro-

pology. She has a broad interdisciplinary background in teaching

and research and has published and presented widely on faculty de-

velopment, instructional strategies, and teaching diverse students.

Address: 301 Rider Bldg II, 227 W. Beaver Avenue, University

Park, PA 16802; telephone: (�1) 814.865.8681; e-mail:

[email protected].


Documents

Investigating the Teaching Concerns of Engineering Educators