New Literacies: Are Colorado Teacher Education Programs Preparing Pre-Service Teachers to Use Technology in Their Learning Environments?

A Dissertation Study - University of Denver - August 2004 - Debra S. Austin, PhD, JD

RESEARCH PROCESS

Method - Educational Criticism and Connoisseurship

The methodology employed in this qualitative study is educational criticism and connoisseurship, a research method developed by Elliot Eisner. Educational inquiry of this type is influenced by assessment and critiques of visual and performing arts as Eisner considers the practices of teaching and curriculum development to be more art than science (Eisner, 1976; Eisner, 1991; Eisner, 1994).

The researcher seeks to discover the relevant qualities of the research subject and explore its significance. To be an effective educational connoisseur, one must possess experience as well as perceptivity to differentiate between subtle and complex qualities of an educational environment (Eisner, 1994). The educational researcher who can perceive and appreciate these kinds of distinctions, and the relationships between these qualities, is a connoisseur. Connoisseurship can be defined as the “art of appreciation” (Eisner, 1998, p. 63).

Eisner has parsed educational environments into several major dimensions: the intentional, the structural, the curricular, the pedagogical, and the evaluative (Eisner, 1998). The connoisseur examines the aims or goals in the setting, but must also be aware of actual practice, as well as the hidden values being diffused. Another aspect of the milieu is its organizational framework. Content and learning activities are considered, as well as the actions of the instructor and mediation of the subject matter. A review of assessment practices concludes the investigation (Eisner, 1998).

Educational connoisseurship is the application of antecedent knowledge of an educational issue to the development of deep understanding of an educational environment. The final responsibility of the educational connoisseur is to disclose the findings of her work. She renders an account of an educational environment through vivid description and detailed appraisal (Eisner, 1998).

The educational critic assesses educational practice through the process of four major phases: description, interpretation, evaluation, and thematics (Eisner, 1998). During the descriptive segment of the study, the researcher uses rich detail to place the reader in the environment and provide a vicarious notion of the surroundings. Interpretation elucidates context and meaning by further unwrapping the complexities of the educational setting and examining their significance. Assessing the quality of the educational practice is the objective of evaluation. Themes are commonalities that may be extended from the studied educational environment to others similarly situated (Eisner, 1994; Eisner, 1998).

This inquiry utilizes description, interpretation, evaluation, and thematics to examine and report on the status of technology education for pre-service teachers conducted in teacher preparation programs in Colorado.

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Conceptual Framework and Research Questions

The primary research question in this study is: 1) What is the state of technology education in teacher preparation programs in Colorado? Four sub-questions guide the inquiry.

A. What leadership, vision, and expectations exist with regard to technology integration in Colorado teacher education programs?

B. What role do teacher educators play in providing technology education to pre-service teachers?

C. What technology curriculum is being provided to pre-service teachers at each institution?

D. What kinds of collaboration are occurring in preparing pre-service teachers to use technology in their teaching?

The secondary research question is: 2) Why does the current state of technology education for Colorado pre-service teachers exist as it does and how could it be improved?

Elliot Eisner’s (1998) major dimensions of schooling provide a primary conceptual framework for analyzing the data in this study. The key dimensions of educational environments defined by Eisner (1998) are the intentional, the structural, the curricular, the pedagogical, and the evaluative. The literature review provided in Chapter 2 rendered four themes which fall within Eisner’s conceptual framework used to examine the data for this study. These themes are: technology leadership, technology teacher educator experience, technology curriculum for pre-service teachers, and collaborative activities which support the technology education of pre-service teachers. Technology leadership and collaborative activities fall under the intentional dimension, while the structural dimension encompasses the role of technology educators and some aspects of the technology curriculum. The teaching dimensions; the curricular, pedagogical, and evaluative, are contained within various facets of the technology curriculum literature theme (see Table 1).

The International Society for Technology in Education has developed a set of standards that guide the practices of specialists within the discipline of Instructional Technology in Teacher Education. The Educational Technology Standards and Performance indicators for All Teachers (NETS*T, 2003) encompass technology applications, the planning and design of educational environments, technology-enhanced pedagogy, technology-enriched assessment practice, teacher professional productivity, and social, ethical, and legal issues associated with technology use (see Appendix C). These standards are blended with Eisner’s teaching dimensions of educational environments and themes from the literature to form the conceptual framework for this study (see Table 1).

Table 1

Dimensions of Educational Environments, Literature & NETS*T Themes

Dimensions of Educational Environments

First, the aims or objectives in an educational environment that are publicized, marketed, and made available to stakeholders comprise the intentional dimension (Eisner, 1998, p. 73). This factor considers what is intended to occur, not what actually does occur. It is possible to determine some of the values at play in an educational setting by exploring the extent to which the intentional goals are revealed and expounded upon. As Chapter Four will show, my analysis of the interviews and artifacts reveals three themes that fall under Eisner’s intentional dimension: statements of intent to incorporate technology into the educational experience of pre-service teachers, plans for faculty development, and the availability of technology education facilities.

The structural dimension, the second to be examined by the educational connoisseur, considers the ways in which an educational environment is organized (Eisner, 1998, p. 74). How technology education is configured for pre-service teachers will impact the ways in which they implement, or ignore, the adoption of technology in their own classrooms. The focus is on the consequences of the exposure pre-service teachers receive, or are denied, to technology in the learning process. Themes which emerge from the data analysis are the existence of a mandatory technology course, the educational level and status of instructors assigned to teach the technology course, and the credits devoted to the course.

Eisner’s curricular dimension, the third in his framework, investigates the significance of educational content and the quality of the learning activities designed to connect students to the subject matter. Antecedent knowledge of appropriate content within a discipline, and its alternatives, is critical to the educational connoisseur’s ability to assess curricular features. She scrutinizes the currentness, complexity, and applicability of the content, as well as its relationship to other subjects. Interview and artifact analysis illuminates the curricular themes of course text selected, content topics studied, and software and hardware chosen for inclusion in the pre-service technology courses, and technology modeling as the method of technology exposure used by some institutions rather than a required technology course.

The fourth aspect of an educational environment that is scrutinized by the educational connoisseur is the pedagogical dimension. The method of delivery or the nature of the mediation of content by the teacher has a significant impact on student learning. The ways in which students experience courses are linked to the nature in which content is taught. The connoisseur looks at the time and emphasis given to particular content, the enthusiasm of the instructor, the clarity of the material presented, and the context in which the instructor must make pedagogical decisions. Since this investigator was unable to observe any technology instruction, the themes in this section will be limited to course descriptions and objectives, course mediation, whether the technology course is offered in an online or face-to-face format, and technology modeling as pedagogy.

Finally, Eisner’s fifth dimension, the evaluative, deals with the impact of evaluation practices on student learning and achievement. Pre-service teachers in Colorado face an assessment environment where content and learning activities are inextricably tied to state standards, while technology lends itself to the completion of project-based, real world assessments. The researcher looks at the nature of the assessments experienced by the pre-service teacher in the technology coursework. The evaluative theme, presented by the analysis of the interviews and artifacts, focuses on the types of assessments completed for the technology course.

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Research Sites and Participants

Research Sites

The research sites in this study are the fifteen schools, colleges, and departments of education (SCDEs) in the state of Colorado that prepare pre-service teachers. Fifteen SCDEs were identified by the Colorado Department of Education (CDE) as the higher education programs responsible for educating the state’s teachers. Barb Lautenbach at the CDE provided the list of the Colorado Council of Deans of Education via email on November 10, 2003. The list was reviewed and two SCDEs were added by the Co-Chair of the Colorado Council of Deans of Education, Dr. Virginia Maloney, that same day. This study revealed that only fifteen of the seventeen SCDEs educate pre-service teachers. The two remaining SCDEs, consisting solely of graduate programs for in-service teachers, were eliminated because the study is examining technology education opportunities for pre-service teachers. Therefore, this study of the state of technology education for Colorado pre-service teachers involved the fifteen data points remaining.

In order to collect as much data as possible from participants at each site, I ensured them that I would not reveal the source of the information, nor would I disclose the identities of my research sites. Pseudonyms may be used to disguise the identities of participants or research sites in order to protect them from any potential harm that sharing data with a researcher might cause (Fetterman, 1998). Pseudonyms could have been used to label quotes taken from interview or artifact data, but they are meaningless unless they continue to be woven through the data. While use of pseudonyms may enhance the reader’s ability to evaluate the specific data per institution, this is not the goal of this study. The objective is to take an initial look at the overall state of technology education for pre-service teachers in Colorado via the fifteen SCDEs that train them. I determined that assigning pseudonyms to the research sites in this study, and labeling relevant data with pseudonyms, would render them identifiable. Therefore, data are presented by theme, and quotes indicate whether the data source is an artifact or interview response.

For the purposes of describing and interpreting my data, I divide the research sites into three groups. The programs that require an Educational Technology Course for their pre-service teachers will be known as the Technology Course Institutions. It is this group of SCDEs that will be the primary focus of the study since there is data to examine with respect to technology education at these sites. Those institutions that do not require a separate technology course, but rely on technology integration, will be called the Technology Modeling Institutions. Teacher preparation programs for which no evidence of a required technology course, nor the practice of technology integration existed in any SCDE web site, artifact, or interview response data are designated the Technology Deficient Institutions.

Participants

The participants in this study are Teacher Education Program Directors, Technology Educators, and Technology Coordinators. In order to identify relevant participants at each SCDE to collect email interview data from, I placed telephone calls to each SCDE’s Dean’s Assistant included on the Colorado Council of Deans of Education list. In each case, the Dean’s Assistant directed me to the Teacher Education Program Director, the Technology Educator, or the Technology Coordinator at the institution. Through artifact review, I identified additional participants not previously acknowledged by the Assistants in the Deans’ offices.

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Data Collection and Schedule

Schedule

Data collection for this study took place from February through May, 2004. I collected two sources of data: interviews and artifacts.

On February 23, 2004, I contacted each SCDE by telephone and requested that the assistant working in the Dean’s office identify the person at their research site who might be able to provide email interview data for my study. I was directed to either the Director of the Teacher Education Program, the Technology Instructor, or the Technology Coordinator for that institution.

Later that same day, February 23, I emailed my Original Interview Protocol to each of the participants identified by the Dean’s Office, at the fifteen research sites (see Appendix A). I received one response to my Original Interview Protocol and it was returned via email in five days.

Immediately after sending out my Original Interview Protocol to the fifteen research sites, I began to collect my artifact data. The first step was to review the entire web site for each SCDE and print anything that was relevant to pre-service teacher education. It was at this time that I was able to determine that a Customized Interview Protocol might be more effective in retrieving interview data from my participants. I developed a Customized Interview Protocol for each SCDE, other than the one institution whose participating technology faculty member answered my Original Interview Protocol (see Appendix B). The Customized Interview Protocols were based on the questions in the Original Interview Protocol, but in all cases I was able to glean data relevant to my study questions during my review of the information on each SCDE web site, therefore resulting in a narrower scope for the Customized Interview Protocols. Through my initial reading of the Faculty Directory Pages for each SCDE, I discovered some additional Teacher Education Technology Faculty, not previously identified by the Deans’ Offices. I believed they might be able to provide additional relevant information for the study than the participants identified by the Assistants to each SCDE Dean. I included this new group of faculty members in my next requests for interview data.

On March 15, 2004, I sent out my first Customized Interview Protocol to a research site. I submitted my penultimate Customized Interview Protocol to a research site on May 3, 2004. My final Customized Interview Protocol was sent on May 10, 2004 to a participant who had responded in February to the Original Email Protocol that she would not be available to participate in the study until after the semester ended on May 8, 2004 (see Table 2). One participant for a research site elected to participate in a personal interview. I used Customized Interview Protocols for fourteen of the fifteen research sites because one participant had responded to the Original Interview Protocol.

Table 2

Interview Collection Schedule

Data Sources

Traditionally, data sources available to the educational connoisseur include observations of educators, interviews with educators, and review of relevant artifacts (Eisner, 1998). This study does not employ observations, which are not compulsory for the completion of a study utilizing educational criticism and connoisseurship (Getz, 1997). Data were collected from two sources: interviews and artifacts.

Interviews

This study was technology-mediated and interviews were conducted via email. Devised to rapidly collect qualitative data from numerous participants who are geographically dispersed, email interviews allow collection of open-ended data through email or email attachments (Creswell, 2002).

This form of interviewing provides rapid access to large numbers of people and a detailed, rich text database for qualitative analysis. It can also promote a conversation between yourself as the researcher and the participants, so that through follow-up conversations you can extend your understanding of the topic or central phenomenon being studied. (Creswell, 2002, p. 207)

Creswell employed this method of interviewing in order to collect data from faculty who teach courses in mixed method research (Creswell, Tashakkori, Jensen, & Shapely, in press). The researchers sent open-ended email interview questions to thirty-one faculty members asking about teaching practices. Sample questions inquired as to the faculty member’s assumptions of why students took courses in mixed method research and what assessment methods were used by those instructors. “This procedure led to a qualitative text database of open-ended responses from a large number of individuals who have experienced mixed method research” (Creswell, 2002, p. 207).

I solicited participants at each of the fifteen research sites for data to be provided via an email interview. I developed an Original Interview Protocol, designed to unwrap the state of technology education at each participant (see Appendix A). I intended to elicit information on the technology vision and leadership at each research site, the role teacher educators play in the technology education of pre-service teachers, the technology curriculum taught at each research site, and any collaborative activities incorporated in each program. None of the potential participants had ever met me prior to the time of the initial requests for email interview data for this study.

My early reading of the artifact data, combined with a lack of response to my Original Email Protocol, led me to the conclusion that Customized Email Protocols might provide greater opportunity for data collection from each research site (see Appendix B). Once I sent out Customized Email Protocols, I began to receive responses to my email interviews. I received Email Interview responses from participants at five of the fifteen research sites which were returned to me via email, with two received from one school. I received one response from a participant via Regular U.S. Mail.

At one research site, the participant responded that she was on sabbatical and would be unavailable to respond to my email interview. A week later, I thought I discovered that this participant would be attending the Society for Information Technology in Teacher Education Annual Conference in Atlanta, Georgia where I was to present a paper. I emailed her to ask for a lunch meeting to enable me to collect data about her institution. When she responded, she told me that she was still in Colorado and that a student had put her name on a paper that was being presented at the conference. I emailed back and extended my invitation to have lunch in Colorado. She agreed and I was able to conduct a personal interview with her.

One participant responded that he would be unable to answer my Customized Interview Protocol questions as he was concerned about my ability to report my findings without revealing the sources of my information or identifying particular SCDEs.

One participant responded the day after I had submitted Original Interview Protocols to all fifteen SCDEs, that he would be willing to answer my Original Interview Protocol questions. Although I sent two follow up emails requesting data from him via a Customized Interview Protocol, he did not respond again nor provide data from his institution.

Without previous introduction or the establishment of a prior relationship with any of the solicited participants, I received interview data from participants at a total of seven of the fifteen research sites, although two faculty members at one site responded, yielding a total of eight interviews. Six participants returned their data via email, one participant returned data via Regular U.S. Mail, and one participant agreed to a personal interview. One participant responded with a refusal to participate; one stated he would participate and yet he failed to; and six participants did not respond in any way to my email interview requests (see Table 3).

There were five Technology Faculty Members (two from a single institution) and one Technology Coordinator who responded to email interviews via email, and one Teacher Education Department Chair who sent his interview responses via Regular U.S. Mail. One Technology Faculty and Department Chair granted me a personal interview. One Technology Instructor refused to participate and three submitted no response. One Teacher Education Department Chair stated he would participate, but did not, and three Teacher Education Department Chairs or Deans failed to respond (see Table 4).

Table 3

Interview Data Responses

Table 4

Interview Participant Type

Interview Response Time

For those participants who chose to answer email Interview Protocols via email, the response time varied from five hours to fourteen days (see Table 5). One participant chose to send his response via Regular U.S. Mail and that took twenty-seven days (see Table 5). The personal interview took place thirty-eight days after my initial email contact via the Original Interview Protocol, however the participant agreed to schedule the personal interview just nine days after initial email contact (see Table 6).

One potential participant answered the Original Interview Protocol with a statement he would participate in the study by answering the Protocol questions. This commitment was made just one day after receipt of the Original Interview Protocol. Although I sent two email requests for information, in the form of a Customized Interview Protocol, this participant did not respond again (see Table 7). Finally, one other potential participant took five days to email me his refusal to participate in the study (see Table 8).

Interview Tables

Table 5

Interview Response Times

Table 6

Personal Interview

Table 7

Willing Participant Who Failed to Respond

Table 8

Refusal to Participate

Artifacts

I collected artifacts from each of the fifteen research sites via a number of different documents available on the SCDE’s web sites. The artifacts, while quite similar in nature, were entitled differently by varying SCDEs. I collected Program Requirements/Degree Plans, Student Handbooks, Academic Catalogs/Course Descriptions, Faculty Directory Listings, Technology Course Syllabi, Technology Course Web Sites, Technology Course Descriptions, PT3 Grant Information, and Technology Vision documents.

The SCDEs in the study vary greatly in the information they make available on the Internet to market their various educational programs. The most common document type available on the SCDE’s web sites was a Faculty Directory of some type, available for fourteen research sites. Eleven sites posted a statement of the Teacher Education Program Requirements or Degree Plan. Nine sites had Technology Vision documents and five had Student Handbooks. Eight had Academic Catalogs or Course Descriptions, four had Technology Course Descriptions, and three had PT3 Grant information (see Table 9).

I was able to review Technology Course Syllabi from six research sites and Technology Course Web Pages from three research sites. Five Technology Course Syllabi and two Technology Course Web Pages were available via individual SCDE web sites. I received access to one Technology Course Syllabi and one Technology Course Web Page from participants at the research sites (see Table 9).

Table 9

Artifact Data

Data for the study was available across all three Technology Education Groups: the Technology Course Institutions, the Technology Modeling Institutions, and the Technology Deficient Institutions. Table 10 is a Data Distribution Table that illustrates how the various data types are arrayed according to Technology Education Group (see Table 10).

Data Type by Technology Education Group

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Data Analysis

Data analysis gives shape to the study and allows what has been discovered to be organized (Glesne, 1999). Current literature guides this inquiry and the report structure for this study is based on the four dimensions of Eisner’s educational critici sm and connoisseurship: description, interpretation, evaluation, and thematics (Eisner, 1998). The conceptual framework, used to organize and analyze the data from the fifteen data points, is Eisner’s five dimensions of educational environments: intentional, structural, curricular, pedagogical, and evaluative (Eisner, 1998) blended with the NETS*T Standards (2003). Data analysis for this study includes coding, the creation of profiles, and themes.

Coding

Coding is the process of reviewing data and categorizing text in order to identify emerging themes (Creswell, 2002; Glesne, 1999). My initial review of the data was the preliminary reading of the web sites of each of the fifteen research sites. I printed everything related to the teacher education program at each institution and filed it in three-ring binders by institution.

I conducted a close reading of the information on each teacher preparation program gathered from the SCDE’s web sites and highlighted all information dealing with technology education for pre-service teachers. My first wave of coding was to categorize the highlighted data according to the four themes identified from the literature review: technology leadership, the role of the technology instructors, the technology curriculum, and collaborative activities that supported the technology education of pre-service teachers. Developing a rudimentary coding scheme can help focus additional data collection and create an early data organizational system (Glesne, 1999). It was this close reading and early coding that assisted in the creation of Customized Interview Protocols for each of my research sites. After receiving responses to these Customized Interview Protocols, I parsed each interview response into the four literature themes. Field notes were taken by hand for my sole in-person interview, transcribed on my computer shortly after the interview, and coded according to my initial organizational literature themes.

Profiles

After creating this initial coding scheme based on the four themes found in the literature, I created profiles for each of the fifteen research sites in order to further unpack the data, to enhance interpretation, and to classify them at a deeper level. Developing profiles allows the researcher to examine the intentions of the participants at the research site in context (Siedman, 1998). By creating profiles for each research site, I could develop a second more specific layer of codes for the data. I turned to my conceptual framework, Eisner’s dimensions of educational environments, for the next phase of coding. Each profile was then re-coded at a deeper level, according to Eisner’s framework, in order to glean the emerging themes. These nascent themes were then developed further using the NETS*T Standards (2003) to identify commonalities and disparities in the data.

Validity

In educational research, the reader must evaluate the credibility and trustworthiness of the work, turning a critical eye to the report as the educational critic has in the studied environment. Validity in educational criticism and connoisseurship can be achieved by viewing the evidence utilized by the researcher through three different lenses: structural corroboration; consensual validation; and referential adequacy (Eisner, 1998).

Structural corroboration occurs when a researcher successfully employs multiple data types to support her interpretation and evaluation of the educational environment. Evidence converges to reveal persistent features and themes in an environment. Ambiguity and uncertainty is likely to remain, but readers look for the tight argument, coherent case, and strength of evidence in appraising the results of research (Eisner, 1998, p. 111).

An educational critic brings her unique experiences, distinctive viewpoints, and particular writing styles to the process of inquiry. Consensual validation considers the extent to which readers find the work persuasive given the reasoning utilized by the critic, the cogency of the argument, the internal coherence, and the personal signature of the writer (Eisner, 1998, p. 113).

The aim of educational criticism is to enlighten the reader, expand perception, and extend understanding of an educational milieu. Interpretation of the context and evaluation of the setting is “referentially adequate when readers are able to see what they would have missed without the critic’s observations” (Eisner, 1998, p. 114).

Member checking is a technique used by educational researchers to lend credibility to the development of profiles. While a valuable tool, member checking is not essential and it is not mentioned by Eisner in either The Educational Imagination (3 rd Edition, 1994), nor in The Enlightened Eye (1998). My participants were assured that I was not going to evaluate individually nor identify their programs in any way. In addition, I received Institutional Review Board approval to explore the state of technology education for pre-service teachers through the identification and examination of patterns and themes in the data. A request to have participants review profiles of their programs in this case would likely have caused considerable concern on their part regarding my research intentions and could have had a chilling effect upon their willingness to further authorize use of the data in my dissertation. Therefore, I did not use member checking in this study.

Metaphor

During data analysis, metaphors were used to distill and compare information from the fifteen SCDE data points. Metaphors provide a way to consider and write about educational environments (Sarason, 1999). They can play a positive role in education research by simplifying and clarifying meaning in a complex milieu (Bullough, 1997). The risk when utilizing metaphors is that the researcher may attempt to inappropriately force a fit of the data into a category, thereby limiting understanding (Bullough, 1997).

Themes

Developing themes was the final stage of data analysis, which aided in understanding the state of technology education for pre-service teachers and answering the questions posed by the inquiry (Creswell, 2002). Themes emerged during all phases of analysis, but reading and reducing the data was critical to the process. I began by using the initial themes from my literature review: technology leadership, the role of teacher educators, the technology curriculum, and collaboration. I determined the relevant information categories and commonalities found in this educational environment by re-reading the interview responses, the artifacts, and the profiles from each research site. Themes matured through the data analysis conducted using Eisner’s five dimensions of educational environments (1998) and the NETS*T Standards (2003). Readers are able to apply these themes to other educational situations through aturalistic generalization (Eisner, 1998). Qualitative research attempts to study a particular case with the hope that the research will “contribute to an understanding of similar cases” (Glesne, 1998, p. 153).

Generating detailed and descriptive profiles of each of my research sites and discovering themes through the process of data analysis aided me in describing, interpreting, and evaluating the technology education programs at each site. Reducing the data in this way unpacks it and provides a vehicle for structural corroboration (Seidman, 1998). Structural corroboration, utilized to evaluate research credibility in educational criticism and connoisseurship, exists when multiple data types are linked to support evaluation (Eisner, 1998). As I was collecting data, analyzing them, and creating thematic profiles, I also developed a Data Collection Profile for each research site. In the Data Collection Profiles, I tracked each email protocol, when it was sent and a response received, and each data source I encountered during my review of each SCDE web site. I have reported the types and numbers of each artifact data source available for consideration in this study, organized by Technology Education Group, to provide its structural corroboration.

Although I developed detailed profiles describing the technology education programs at each teacher preparation institution in Colorado, my study maintains the confidentiality of my participants and the anonymity of my research sites. I believe I received more candid responses to my interview questions and was given greater access to documentation by providing participants of the reassurance that the particular state of their technology education program would not be divulged.

I am interested in the progress that Colorado teacher preparation programs are making in their efforts toward technology education for pre-service teachers. This process is challenging, may be expensive, and can present difficult issues. Technology education programs may not be fully developed or in the condition intended by administrators and faculty.

On the other hand, I believe this topic to be of interest to all my research sites and I intend to offer each site a copy of my research findings. My report of the general state of affairs of technology education for Colorado pre-service teachers may assist each program in examining their progress in the process of providing technology education to pre-service teachers.

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Researcher

My orientation toward technology comes from an interest in doing a better job at my life’s work. That work has changed over time, but for most of my career, it has involved teaching. As a forty-four year old Colorado native, I did not grow up with computers, nor did I use one in my first job teaching middle school in a Denver suburb. I did not learn how to use a computer until I was in law school. The law firm I was clerking for put one in my office and I was enthralled. It was immediately apparent that the computer would improve both my work and school tasks.

Upon graduating from law school, I took a position with a legal research company, first selling research resources on CD-ROM and then training lawyers to use an electronic research service. This work combined my established interest in teaching with an emerging fascination regarding the potential of computers. I made commissions when customers used the research service, so I spent a lot of time thinking about how to make computer usage easier.

After seven years of conducting sales and training sessions in most of the western states, I was given the opportunity to work in the Law Library at the University of Denver. My new challenge, incorporate legal research instruction into the law school curriculum. Legal research is arguably the least sexy law school content, yet one of the most important knowledge and skill sets necessary for the practice of law. I identified computer technology as the key component in developing an innovative and appealing legal research curriculum. I started with PowerPoint, but knew the Internet was my target media. For four years, I have been teaching the Advanced Legal Research course to mostly packed houses using a self-developed web site as my text and technology-based student assessments. I have also had the opportunity to work with teachers and librarians in a course on incorporating technology in K-12 learning environments for three years. The practices of designing technology-based curriculum, presenting content using technology-enhanced pedagogy, mentoring students while they complete technology-enriched assessments, and reflecting on the potential for improvement in the next semester have become my passion.

It is enhancing the relationship between the student and the content that captivates me. My strong focus on that relationship helps me maintain an ongoing interest in new technological tools and their potential uses in education. For me, inquisitiveness far outweighs the obstacles present when learning and utilizing new devices. The teaching and learning process is complex and not entirely understood. As a learner, I am much more engaged in a process of deep exploration and project production than an exercise in memorization. I am more likely to integrate knowledge into my practice if I have had a chance to develop an intense and meaningful relationship with it. I believe these characteristics to be true of all learners and I believe American education is poised to take the next step in its ongoing evolution.

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Innovation in Data Collection

The method of digital data collection utilized in this study is novel and appropriate for a study concerning technology in education. The data collected are interview responses and artifacts and they were gathered using email requests for both interview responses and artifacts and an exhaustive review of the web sites of the fifteen study institutions. I received interview responses both electronically and via the US Mail. I received access to artifacts via email attachments, publicly-available SCDE web sites, and privately-secured course web sites. Combining digital data collection with the educational criticism and connoisseurship methodology is unique as well.

Email Interviews

John Creswell has used email interview protocols in at least one of his research projects and approves its use for rapid collection of rich qualitative data from participants who are not easy to interview in person due to geographic challenges. He also points out that a conversation can be achieved in cyberspace, just as in a personal interview (Creswell, 2002). The success of this technique depends to a large degree on the researcher’s ability to foster a sense of digital collegiality with a participant, the participant’s interest in the subject of the study, or the nature of the relationship between the researcher and the participant. It is more likely that a potential research participant will respond diligently and amiably to a request from a famous educational researcher or well-known colleague than to an unknown doctoral student. Email is an adroit technique to continue an exchange begun in a personal interview and was also useful in this inquiry.

In this case, I was unknown to all participants in the study. My Original Interview Protocol was an email attachment that included a small picture, biographical information, and a web site address to my Online Teaching Portfolio so that my potential participants could assess my background and make an informed decision regarding participation in the study. My email address includes the .edu suffix indicating my relationship with an institution of higher education. Participants could easily check the University of Denver web site to confirm I am employed there.

Another major consideration for participants is whether they trust a researcher to do what they say they will do with the information they are seeking. I had to convince participants that I had no intention of evaluating individual programs, nor would I identify their programs in my dissertation. In fact, one potential participant did not believe I could report on this topic without revealing the identity of the teacher preparation programs and declined to participate. The incorporation of technology into teaching in a higher education environment and into teacher education curriculum is a political and sensitive issue and some participants simply may not have wanted to discuss the state of affairs at their institution.

Finally, participants must consider whether they want to spend the time thinking about the questions and answers, gathering the artifacts, and drafting an email response. Those participants that did respond seemed quite interested in the research topic and also answered affirmatively to my offer to provide them with a copy of the completed study. Their curiosity about the topic combined with their attitude about professional responsibility with regard to knowledge production seemed to outweigh the burden of completing the interview protocol and request for artifacts.

Digital Artifacts

The production of digital artifacts requires little effort if they are Word or PDF documents or available on a web site. They can be sent to a researcher with ease as an email attachment by a willing participant. Gathering data of this type involves the same participant concerns as noted in my discussion of email responses. However, I was quite surprised at the volume of artifacts available on SCDE web sites. When I did not receive a response to the Original Interview Protocol and upon beginning my review of SCDE web sites, I realized that many of my questions would be answered utilizing the information found there. I also knew immediately that I could reduce the amount of work required of my participants by customizing my requests. Finally, rather that using an email attachment for my questions and artifact requests, I put the text of my requests directly into the email for the Customized Interview Protocols. I included an estimate as to how much time I thought it would take to respond to my questions. A potential participant could evaluate fairly quickly whether to participate or not.

Digital Data Collection and Educational Criticism

The confluence of digital data collection and the educational research methodology educational criticism and connoisseurship is rare, if not unique to this study. The concerns revolve around what we think of as an educational environment, what has come to be expected in an educational criticism description, and the assessment of qualities inherent in information examined by an educational connoisseur.

The most commonly studied educational environments are classrooms and schools. A material setting seems to be tied to Eisner’s methodology, yet much information is available to be considered by the educational researcher. In the Information Age, it is not imperative to be situated in an environment to study it, just as it is not essential to learn in person in a classroom.

Then there is the matter of portrayal. There is almost no limit to the quantity of description one can render of a physical environment. Readers of educational criticism may yearn to read about physicality; however, this demonstrates a bias for the visual. The electronic word was the source of information about the educational environment in this study, although access to digitized text was garnered using a variety of techniques. Perception in the age of digitality is akin to visualizing the spiritual.

This maiden inquiry into the state of technology education for pre-service teachers in Colorado utilized the types of electronic resources I have been manipulating for six years to improve my instruction and enhance the learning environments of my students at an institution of higher education. The methodology was particularly germane given the fifteen geographically dispersed data points in the jurisdiction of interest and the reluctance of a portion of the participants to reveal the state of affairs at their institution. Many of the resources referenced in the literature review are in digital format on a variety of government and organization web sites. The electronic word will allow me to extend my relationship with study participants, and perhaps with those who opted out of this initial examination, by sharing the findings via a web site I intend to create. This will link the reader from the research to much of the literature with a single click. Given the cutting-edge context of this study, it strives to achieve the chief aim of educational criticism, to inform readers and expand their understanding of the state of technology education for Colorado’s pre-service teachers.

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Limitations of the Study

The major limitation of this study was inequitable access to data from all fifteen of the research sites. Each SCDE maintains different kinds of information on its web site. While there was much information for each SCDE, it was varied in its type. This led to inconsistent artifact data collection across all research sites. In addition to the artifacts available on the SCDE web sites, I relied on a digital collegiality among participants with whom I had no prior relationship. I approached Teacher Education Program Directors and Deans, Teacher Educators, and Technology Coordinators for information on their technology education programs for pre-service teachers via email requests for information. Their reaction to my requests varied. If all participants had been willing to answer my questions, the interview data would have been stronger. Consistent interview and artifact data from all fifteen SCDEs that prepare pre-service teachers in Colorado would have provided a more complete picture of the state of technology education for new teachers.

A second limitation is related to the first. This inquiry was conducted using data from research sites and participants with whom I had no prior relationship. It is likely I requested information from some participants reluctant to provide data for a study on a compelling, yet potentially highly-charged educational issue. Eight potential participants either refused or elected not to answer email interviews. There may be many reasons for this lack of response, but it is logical to assume that some participants simply did not want to divulge information about the state of technology education efforts at their research sites.

A third limitation was the burdens that confidentiality and anonymity placed on reporting my findings. Creating a profile for each educational institution would have provided a clearer picture of the individual progress made in technology education of pre-service teachers. Contrasts and comparisons could have been drawn between institutions. The report in this case is focused on educational patterns, trends, and themes. This limitation is offset by the increase in amount and quality of data I believe that I was able to obtain by assuring the confidentiality of information and anonymity in reporting. Ultimately, in presenting the data I am not able to treat each of the fifteen SCDEs as case studies, but to discuss the state of affairs within one jurisdiction, the state of Colorado.

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