Para los resultados del segundo objetivo

Measuring Design Self-Efficacy (DSE) in the context of architectural design studios and understanding the influence of studio type, project type, and student

predispositions on those measures is the primary interest of this research. Initial drafts of the instruments were used in a pilot study that was completed in the spring 2015

semester at the University of Kentucky. This process included a test/re-test of survey questions and exit interviews with high-performing students (students who had high design studio grades) and low-performing students (students who had low design studio grades) to ensure that the phrasing of the questions was clear and that the students could understand what was being asked of them.

III.5.1 Spring 2015 Pilot Study

demonstrates impact on student self-efficacy and communication. The results of the Spring 2015 pilot study were evaluated during the Summer 2015. Additional IRB applications at TAMU (TAMU IRB#2015-0860D) (Appendix 15)and UKY (UKY IRB#15-0680-P4S) (Appendix 16)were submitted in the Fall 2015 semester. These IRB applications were approved prior to the beginning of the Spring 2016 semester. The University of Kansas did not require an IRB to extend the study to its campus. This survey instrument was fully deployed in the Spring 2016 semester and the data collected for the final study.

The experimental unit for the pilot study was a student-by-project with repeated measures of the students at the beginning and at the end of the semester. To establish a baseline measure of Design Self-Efficacy (DSE) and predisposition for collaboration (PD) a “test in” at the beginning of the semester was given to students prior to the faculty presenting a studio problem. After the final review self-efficacy and

predispositions were measured again along with studio type (ST) and project type (PT). By gathering research data in this manner, sample data defined the studio as a way of understanding both ST and PT while gathering DSE and PD measures for the students throughout the semester. At the conclusion of the data collection phases, these

differences were statistically analyzed and tested for correlation. III.5.2 Spring 2015 Preliminary Results

The results of Spring 2015 pilot study entitled: “Interdisciplinary Exchanges in a Design Studio Context: Student Efficacy and Knowledge Transfer” developed in

Communication and Research in the School of Information Studies and Mary Ann Nestmann, the Instructional Technology Manager for PresentationU at the University of Kentucky, suggests that there is strong evidence for correlation between student

responses to questions related to Design Self-Efficacy and the processes of typical architectural design development and communication. Because the sample size was lower than the number of question items in the instrument, there were limitations in the number of statistical conclusions that could be made.

However, there appeared to be four emergent groupings of questions that strongly correlate (.7 or above in a 35x35 analysis). These groupings separate into four categories: Research, Design, Evaluation, and Communication.

1. Group 1 – Research

a. DSE_10 - Ability to connect design precedents to the design project, b. DSE_16 - Ability to identify relevant precedent for a project,

c. DSE_20 - Ability to construct models that illustrate and identify all necessary information for a building design,

d. DSE_13 - Ability to collect relevant information to support conclusions related to a specific project,

e. DSE_26 - Ability to predict the effectiveness of a design if implemented

2. Group 2 – Design

b. DSE_27 - Ability to make design decisions in complex project whiles considering the variety of influences (e.g. accessibility, environmental systems and structural systems),

c. DSE_29 - Ability to respond to site specific characteristics in my design

3. Group 3 – Evaluation

a. DSE_18 - Ability to create technically clear drawings, b. DSE_19 - Ability to prepare outline specifications, c. DSE_33 - Ability to establish required points of exit, d. DSE_34 - Ability to check egress paths for travel distances 4. Group 4 - Communication

a. DSE_1 - Ability to use effective oral communication that is appropriate for other people within the profession

b. DSE_2 - Ability to use effective oral communication that is appropriate for the general public

c. DSE_6 - Ability to use representation media (i.e., models and drawings) that are appropriate for the general public

Early evidence suggests that design self-efficacy question items DSE_4 - Ability to write effectively for the general public, DSE_14 - Ability to use formal,

organizational, and environmental principles to inform my design, and DSE_15 - Ability to apply fundamental ordering principles to natural and man-made systems do not correlate strongly (less than .3 in a 35x35 analysis) with each other.

The emergence of four groupings and categorizations—Research, Design,

Evaluation, and Communication—was then compared against the theoretical grouping of three essential skills and abilities developed by Bernard Hoesli at the University of Texas in the 1950s: the evolution of a design, in architectural terms, that responds to design constraints, building program requirements, and structure, that is conveyed in terms of models and drawings (Caragonne, 1995). For this research, these theoretical categories align to NAAB SPC as a consistent framework for analysis of evidence (Appendix 10).

III.5.3 Impact on Final Study

By conducting the pilot study, four topics were introduced into the final study: a confirmation of NAAB SPC mapping of student learning outcomes to task-specific DSE questions, reverse coding of questions, the introduction of a predispositions survey instrument, and the use of a data broker. The constructed DSE measurement instrument was developed in alignment with Bandura’s self-efficacy assertion (Bandura, 2006). This instrument used the tasks dictated by the 2014 NAAB SPC as a structure for assessing evidence of understanding and ability of design knowledge for all students enrolled in the accredited programs of architecture. The SPCs are mapped across all design studio levels, regardless of context (studio types) and project types to see if certain criteria are weighted differently.

In the initial self-efficacy survey instrument all of the questions were positively coded and delivered in a continuous question and answer screen. It has been suggested

questions into smaller groupings could better focus student’s attention. To address this issue, some of the existing questions were reverse coded and reorganized in the Qualtrics survey to enhance usability (Appendix 09).

In order to better understand a student’s predisposition for collaboration, an individualism and collectivism instrument was inserted into the DSE instrument so that students could self-report their scores.

Also, in order to develop the comprehensive final data collection and analysis, a trusted data broker from each of the respective University was recruited. These data brokers were charged with emailing the panel survey, assigning anonymous coding to de-identify data, uploading the panel data to Qualtrics, and then linking it to institutional data such as demographics. In doing so, the data brokers enabled the researcher to analyze the data in compliance with the IRB and focus on the results without confounding the study.