This mixed methods research study examined the relationship between faculty mindset and their perceived use of instructional technology in the higher education classroom. Recognizing the growing importance of technology-mediated learning interventions, the researcher sought to gain a deeper understanding of how mindset influenced the use of technology particularly amongst college of education faculty in Florida public 4-year universities. Data analyses revealed the following findings: (a) Although participants shared a range of integration patterns, faculty predominantly integrated technology for knowledge transmission, backstage activity, and communication purposes; (b) Participants predominantly occupied the integration phase of technology implementation, suggesting that they used technology committedly, but in ways that were familiar and common; (c) The way participants perceived and approached technological realities influenced their patterns of technology integration; and (d) Faculty shared similar concerns about the challenges and benefits associated with technology integration in their classrooms. The key implications that emerged from this study were that student-centered technology implementation practices were underrepresented, and that faculty seemed ill-equipped or underprepared to implement strategies surrounding accessibility. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

No description available.

A variety of software tools and guidelines have been developed to help students diagram, analyze, and better understand complex arguments. However, little or no empirical evidence exists to validate whether the processes embedded within existing tools and guidelines are processes that produce better argument diagrams. As a result, the purpose of this study was to determine: 1) the mapping and reasoning processes used by experts and novices to analyze complex arguments; 2) how the processes performed by experts versus novices differ; and 3) based on the observed differences, identify the processes that facilitate and hinder more accurate argument analysis. The verbal reasoning and argument-diagramming processes of four experts in argumentation and five novices across four different graduate programs were recorded on video as they constructed their argument maps using a diagramming software application called jMAP and as they verbalized their thought processes in a think-aloud protocol/interview. Sequential analysis was used to identify and differentiate the sequences of mapping actions used by experts versus novices and the sequences of mapping actions that were used to produce the highest versus lowest quality argument diagrams. The findings from this indicated that the experts' processes for positioning, linking, and reviewing nodes produced more accurate maps than the processes used by novices. Based on these findings, I discussed several possible interpretations of the four experts' reasoning processes in the context of argument diagramming tasks and in the context of more global reasoning processes identified from a qualitative analysis of the video recordings and verbal protocols. Lastly, I presented several educational implications with regard to using the experts' processes as a model for scaffolding and helping students better analyze and evaluate complex arguments and for designing diagramming software. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the Doctor of Philosophy. / Spring Semester, 2015. / April 13, 2015. / argument analysis, argument diagram, argument map, critical thinking, expert novice, reasoning process / Includes bibliographical references. / Allan Jeong, Professor Directing Dissertation; Michael Kaschak, University Representative; Valerie Shute, Committee Member; Vanessa Dennen, Committee Member.

Three studies were conducted to better inform how instructional design of educational programming for children impacts learning. In these studies, we focused on how unplugged debugging activities, which require correction of coding errors, affect skills related to computational thinking and personal attributes of children. Study 1 observed debugging performance across varying degrees of embodiment (full and low) with a control group. To identify and rectify coding errors, children in the full embodiment group walked on a floor maze whereas low embodiment group manipulated a paper character using their fingers. Study 2 examined the effects of different degrees of embodiment when combined with either coding or narrative based language on computational thinking and self-efficacy. Children fixed coding errors on a worksheet using coding language or narratives, then performed their revised code using full or low embodiment. Study 3 explored whether congruent or incongruent hand gestures incorporated with either direct or surrogate embodiment enhanced children’s graphic and text programming, self-efficacy, and persistence. In the congruent gesture group, participants placed coding blocks in the same direction that the programming character moves whereas incongruent gesture placed coding blocks in a linear fashion. Direct embodiment is where the participant uses their finger to move a character whereas surrogate embodiment is where the researcher is controlled by the participant through verbal commands. The results on computational thinking skills were: 1) Children performed better in debugging and problem solving using low embodiment; 2) Programming efficiency increased with the use of coding language; 3) Higher performance on graphic programming was found with incongruent gesture while transfer from graphic to text programming improved with surrogate embodiment. In personal attributes: 1) Significant interaction effect was found between hand gesture and embodiment on self-efficacy; 2) Higher persistence was exhibited from direct embodiment. These findings between embodiment and development of computational thinking skills and personal attributes may be utilized in the unplugged learning environment. This is particularly relevant in supporting students to acquire basic computational thinking skills where relevant technology resources are not available.

Technology experts suggest that one barrier in implementing technology has been a lack of appropriate training for teachers. Past efforts have been few in number, poor in quality, and uncoordinated. Some large school districts are developing comprehensive programs. However, few models exist and none are suitable for small school districts. The purposes of this study were: (1) to survey 53 small school districts in Texas to identify hardware and software configurations, patterns of recent technology staff development, and needs for future technology staff development; (2) to design a staff development program which addresses these technology needs; and (3) to evaluate the program in a small school district.

The purpose of this study was to analyze teacher perceptions on the relationship of technology and student academic behaviors and performance in the blended learning environment across 9th through 12th grade within east Tennessee and to identify the components of blended learning and pedagogical practices that enhance students’ academic behaviors. Specifically, this study is an analysis of how student motivation and student autonomy relate to technology implementation and face-to-face instruction within blended learning environments. The participants of this study were teachers within 2 school districts in East Tennessee. All high school teachers within the participating school districts received an online survey that was distributed from their corresponding principals via email. The online survey used a Likert-type scale that consisted of 40 items focused on teachers’ perceptions of student motivation and student autonomy with the blended learning environment. The analysis of the data was based on the responses of 75 teachers from the 2 participating school districts. Statistical analyses of the data revealed that the amount of teacher technology use, student technology use, learning management system use, and type of professional development did not have a significant relationship with participants’ perspective of student motivation or student autonomy. The research also did not reveal a significant relationship between participants’ age and perception of student motivation. However, this research revealed a significant relationship between participant age and participants’ perception of student autonomy. The study revealed that, as participant age increased, participants’ mean student autonomy scores decreased.

Accessibility and usability of software define the programs used for both professional and academic activities. While many proprietary tools are easy to grasp, some challenges exist in using more technical resources, such as the statistical programming language R. The creative project tidyTouch is a web application designed to help educate any user in basic R data visualization and transformation using the popular ggplot2 and dplyr packages. Providing point-and-click interactivity to explore potential modifications of graphics for data presentation, the application uses an intuitive interface to make R more accessible to those without programming experience. This project is in a state of continual development and will expand to cover introductory data science topics relevant to academics and professionals alike. The code for tidyTouch and this document can be found at https://github.com/devaneyJE/tidyTouch_thesis (see ui.R and server.R files for application code).

Reports and surveys by the U.S. government and international organizations have repeatedly acknowledged the achievement problem in math in K-12 regardless of various efforts (e.g., by the U.S. Department of Education) to diminish it. To address the problem in math achievement in K-12, teachers, scholars, and the U.S. government have developed various materials and intervention tools. As a potential platform to address the problem in math achievement, video games generate a large variety of perspectives on their value. Along with the debate on the game's inherent good or bad features, there is also a debate on the effectiveness of video games as a learning tool. Regarding these debates and the ambiguous results on video games as learning tools, Greitemeyer and Mügge (2014) postulated that games can provide both positive and negative impacts according to their content (i.e., violent and pro-social games). However, recent literature investigating the use of video games in varied learning contexts shows that the learning effectiveness of games is still inconclusive. A potential reason is that video games mostly facilitate implicit qualitative understanding. Video games consist of rich interactive experiences that help to foster understanding of qualitative relationships in gameplay more than quantitative proficiency that is required in the formal school system (Clark et al. 2011; Squire, Barnett, Grant, & Higginbotham, 2004). Another reason is that educational game designers have paid little attention to designing and developing learning supports in educational games. Therefore, the current study aims to address a comprehensive question -- How does an educational game, through the use of learning supports, promote the application of acquired qualitative understanding to math problem solving in formal educational contexts? A promising method to address the aforementioned problem is to externalize cognitive and metacognitive processes (Lajoie, 2009). Externalizing Problem Representation (EPR) refers to a cognitive behavior in which a learner constructs her own representations overtly (Cox, 1999). The processes of EPR are to re-order information in problem solving, to clarify ambiguous parts of the problem, and to modify and enact mental representations including mental animations and images. EPR helps to make missing and implicit information or representations explicit. There are several synonyms of Externalizing Problem Representation (EPR), such as external representation (Zhang, 1997), externalized cognition (Cox & Brna, 1995), and re-representation (Ainsworth & Th Loizou, 2003). From the semiotics perspective, EPR can be categorized into two forms by its sign: Iconic and symbolic. Although the potential benefits of externalizing problem representation was claimed in prior research, little attention was paid to investigating the design of EPR in video games. Compared to the studies of mental problem representation, few empirical studies on external representation have been conducted. Hence, it is warranted to examine the efficacy of learning support that promotes externalizing problem representation in two formats (i.e., iconic and symbolic) in the video-game-based learning setting. In light of this, the purpose of this study is to investigate whether EPR-promoting scaffolds (in iconic vs. symbolic formats) enhance qualitative understanding and quantitative proficiency in ratios and proportional relationships in a learning game context. Specifically, the learning game will request players to respond to either iconic or symbolic learning probes that help to externalize the mental representations of the math problems in the game. In this study, quantitative proficiency refers to the problem solving proficiency in both game and formal education context. The current study involves two levels of task complexity (i.e., low complexity vs. high complexity) as a moderating variable. The study addresses the following research questions: 1. Will iconic learning probes promoting EPR enhance qualitative understanding and quantitative proficiency in ratios and proportional reasoning, with the task complexity controlled in the educational game? 2. Will symbolic learning probes promoting EPR enhance qualitative understanding and quantitative proficiency in ratios and proportional reasoning, with task complexity controlled in the educational game? 3. Will iconic learning probes promoting EPR, in comparison to symbolic learning probes promoting EPR, be more effective in enhancing qualitative understanding and quantitative proficiency in ratio and proportional reasoning, with task complexity controlled in the educational game? To accomplish the purpose of this study, learning probes that prompt learners to externalize their internal problem representation were developed in two different formats, iconic and symbolic, based on Mayer's math problem representation model. In the experiment, forty-five participants in this study processed either iconic or symbolic learning probes during their gameplay. Finally, qualitative understanding and quantitative proficiency were measured three times: before this study, after playing the shipping container episode with a low complexity task, and after playing the shipping container episode with a high complexity task. Regarding Research Question 1, the result of repeated-measures ANOVA indicates that, for participants in the Iconic Learning Probe (ILP) group, the difference in qualitative understanding between the pretest, posttest, and posttest 2 was not statistically significant whereas the difference in quantitative proficiency between the pretest, posttest 1, and posttest 2 was statistically significant. Regarding Research Question 2, the result of repeated-measures ANOVA indicates that, for participants in the Symbolic Learning Probe (SLP) group, the difference in qualitative understanding between the pretest, posttest 1, and posttest 2 was statistically significant whereas the difference in quantitative understanding between the pretest, posttest 1, and posttest 2 was not statistically significant. Regarding Research Question 3, since there was a significant interaction between the times of measurement and the types of EPR in regard to both qualitative understanding and quantitative proficiency, pairwise comparisons using the Bonferroni method were drawn. There were significant differences in participants' qualitative understanding between ILP and SLP groups in posttest 1 and posttest 2 whereas there was no significant difference in participants' qualitative understanding between ILP and SLP groups in the pretest. Regarding the quantitative proficiency, there were significant differences in participants' quantitative proficiency between ILP and SLP groups in posttest 1 whereas there was no significant difference in participants' quantitative proficiency between ILP and SLP groups in the pretest and posttest 2. In the final chapter, I discussed major research findings of this study based on the theoretical research reviewed in Chapter 2. Then I described the implications of this study and suggestions for future study. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2016. / January 12, 2016. / Includes bibliographical references. / Fengfeng Ke, Professor Directing Dissertation; Gordon Erlebacher, University Representative; Valerie Shute, Committee Member; Vanessa Dennen, Committee Member.

<p>  </p> <p>The concept of computational thinking (CT) has become more prevalent across the engineering education research and teaching landscape. Yet much of the research to date has been more definitional and has not offered many ways to convert CT theory to practice. One prominent set of tools used across engineering disciplines is modeling and simulation, which allows students to create a representation of the outside world as they understand it. </p> <p>This three-paper dissertation connects modeling and simulation skills with eliciting CT by leveraging model-based reasoning as a theoretical framework. A learning design was created and delivered here via design-based research that includes educational frameworks such as productive failure and model-eliciting activities (MEAs) to structure the modeling activity within a classroom setting. The designed learning intervention used a four-part sequence to scaffold the modeling activity in the classroom: (1) planning the model, (2) building the model, (3) evaluating the model, and (4) reflecting on the model. A case study of a final-year capstone course in biological engineering implemented the four-week designed learning intervention as part of the course. </p> <p>The guiding research question for the study was <em>how do modeling and simulation activities elicit computational thinking practices in the context of undergraduate engineering education? </em>To approach this question, data were collected in audio transcripts and student-generated artifacts to identify areas where the modeling activity elicited different forms of CT in the student work. The first study examined how CT was elicited within the model-building phase and developed an initial codebook for CT practices and outcomes using thematic analysis. The second and third studies built upon that codebook and further the outcomes by analyzing the modeling activity's planning and evaluating/reflecting phases. The results indicate that CT is used throughout the entire modeling and simulation process as students engage in model-based reasoning. The identified CT practices of abstraction, algorithmic thinking, evaluation, generalization, and decomposition emerged from a thematic analysis, and each practice was further characterized and refined into a set of outcomes. Furthermore, each phase of the modeling activity emphasized unique CT outcomes suggesting that students would benefit from enacting the entire modeling and simulation process to acquire and practice a diverse range of CT outcomes. </p>

Artificial Intelligence (AI) is the way forward in accounting and auditing. The purpose of this study was to examine the relationship between accounting students’ level of technology readiness (TR) and AI technology adoption (TA). This quantitative study examined the independent variables of TR, perceived ease of use (PEOU), and perceived usefulness (PU) and the dependent variable of TA. Moreover, the present study examined the mediating effect of PEOU and PU on the relationship between TR and TA. The present study was related to individual accounting students’ perceptions of TR and TA. Student participants (n = 101) recruited for this study were randomly sampled from 2 universities in Southern California, the United States. An online questionnaire consisting of 30 items regarding perceptions of TR, PEOU, PU, and TA was administered. The bivariate correlation and regression between variables showed that TR, PEOU, and PU positively influence TA; TR positively influences PEOU and PU; and PEOU positively influences PU. Mediation analysis showed that both PEOU and PU mediate the relationship between TR and TA. Because of the significant relationships among variables, the model met the criteria for technology readiness and acceptance model (TRAM) and Model 6 of process mediation. This study adds to the empirical research regarding the relationships between the constructs of TR and TA of AI within higher education, in which there is a gap in the literature. The study contributed by applying the TRAM construct to the use and adoption of AI. TR, PEOU, and PU are important constructs within higher education and predict AI TA by accounting students. Additionally, TR is a precursor to PEOU and PU of AI for this population. For practice, universities should enhance use perceptions by creating opportunities for accounting students to interact with AI. Effective adoption of AI in accounting curricula aimed at enhancing students’ perceptions is essential to increase their adoption of AI and overall career readiness. For research, replicating the study at other universities, examining other factors that influence students’ adoption of AI, and exploring other AI topics in higher education could expand the literature on technology readiness and TA of AI.