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Social robots have the potential to play a vital role in education. Student technology acceptance may be considered as a driver for their successful integration in educational processes. Based on the ICAP (Interactive, Constructive, Active, Passive) framework and research on social robot roles, we have developed eight vignettes describing scenarios for the use of social robots in higher education, e.g., teaching assistant. Students in an introductory university course completed the vignettes; they answered questions based on the unified theory of acceptance and use of technology (UTAUT), as well as on their ethical approval. Drawing from a sample of N = 361 students, we carried out confirmatory factor analysis. In line with the conceptual basis, eight scenarios can be described. Overall, students do not accept social robots as presenters; however, the assessment of other roles, such as teaching assistant, is positive. By means of a latent profile analysis, we were able to identify four profiles that may be meaningful from a conceptual point of view. One profile is particularly noteworthy. It comprises students who accept social robots not as a means of instruction, e.g., as a tutor, but as a tool, e.g., to promote computational thinking.

Far-reaching technological changes are shaping our society and the ways in which we work. A key 21st -century skill for taking advantage of those changes may be computational thinking (CT). CT aims at enabling humans to carry out more effective problem solving by utilizing concepts of computing and computer technology. For a successful integration of CT into curricula, however, it is important to take assessment into account. We review two instruments that capture CT: the Computational Thinking Test (CTt), a performance test, and the Computational Thinking Scales (CTS), that relies on self-assessment. We have adapted both instruments from English to German. Using a sample of 202 upper-secondary students from Switzerland, we provide further evidence on the validity of both instruments. To this end, we apply item response theory and confirmatory factor analysis. Furthermore, we evaluate the relationship between CTt and CTS. Both instruments show good properties and may be suitable for assessing CT in German-speaking countries at the secondary level. [For the complete proceedings, see ED608557.]

Digital transformation shapes the educational system in many ways. It has also far-reaching implications for teachers as their job description may fundamentally change in the future. In this light, it is important 1) to identify necessary digital competences of teachers and 2) to find ways to foster those competences in an efficient way. By means of a literature review and expert interviews, we developed a framework of teachers' digital competences. In line with Baumert and Kunter (2006) as well as Koehler and Mishra (2009), it comprises content knowledge, pedagogical content knowledge, and pedagogical knowledge. However, these facets have extended meaning in the context of digital transformation. Moreover, our framework considers the official EU competence framework (Carretero et al., 2017) and hence covers instrumental skills and knowledge in handling digital media. We successfully validated our framework by means of structural equation modelling with a sample of 215 Swiss teachers. Utilising an Importance Performance Map Analysis, we identified competence facets that show the highest effects on the (self-reported) use of digital media and content. For efficiently fostering those facets, we will establish online professional learning communities consisting of a communication platform, webinar series, and blended learning courses. [For the complete proceedings, see ED600498.]

Technological advancements, particularly in artificial intelligence, significantly transform our society and work practices. Computational thinking (CT) has emerged as a crucial 21st-century skill, enabling individuals to solve problems more effectively through an automation-oriented perspective and fundamental concepts of computer science. To ensure the effective integration of CT into educational curricula, it is crucial to develop efficient assessment frameworks that allow teachers to measure and promote student CT proficiency. Therefore, our aim is to develop a short test to measure CT among undergraduate students. To this end, we consider two performance tests: the Computational Thinking test (CTt) and the Algorithmic Thinking Test for Adults (ATTA). We use items from both instruments to compile a short test. Based on a sample of 290 second-year non-computer science undergraduate students, we provide evidence on the quality of our test. Besides classical test theory, we apply item response theory, namely Rasch modeling, and confirmatory factor analysis. Our test shows favorable properties, e.g., Cronbach's alpha > .75, and may be suitable for the efficient assessment of CT across higher education programs. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is an important 21st-century skill. This paper aims at investigating predictors of CT self-efficacy among high-school students. The hypothesized predictors are grouped into three areas: (1) student characteristics, (2) home environment, and (3) learning opportunities. CT self-efficacy is measured with the Computational Thinking Scales (CTS) that comprises five dimensions: creativity, algorithmic thinking, cooperativity, critical thinking, and problem solving. N = 202 high-school students act as the sample, linear regression as the analysis method. The best prediction is possible for algorithmic thinking (R² = .511). For cooperativity, the explanatory power of our model it is weak (R² = .146). Across all five CTS dimensions, CT self-concept is the best predictor for CT self-efficacy. [ABSTRACT FROM AUTHOR]

Perceived personality plays an important role in human-robot interaction. This paper uses the Big Five Inventory–2 (BFI-2-S) to assess the perceived personality of a type Pepper social robot. Pepper provided a sample of its capabilities during an introduction to academic writing university course. N = 462 students evaluated Pepper’s personality by answering the BFI-2-S questions. A confirmatory factor analysis with the implied five-factor structure did not converge. A subsequent exploratory factor analysis yielded inconclusive results. Although we were not able to provide evidence for a Big Five personality structure of the social robot, perceived personality may be an important characteristic of a social robot: The latent correlation of a factor labeled ‘positive characteristics’ with the intention to use the robot equals .487. [ABSTRACT FROM AUTHOR]

During the last number of years, States' support for higher education has declined significantly. Over the next decade, higher education will continue to face the challenges of state revenue funding constraints, changes in the public perception of higher education, and the effectiveness of higher education in preparing young men and women for a career after graduation. With their natural connection to industry, engineering and construction education programs are poised to lead the way in a new model for the future of higher education. Construction management education by its nature is connected to the construction industry. In fact, construction management was created by the construction industry. As a result, today graduates from construction management programs across the U.S. enjoy almost 100% employment, higher salary than many other disciplines, and a great career. Construction management however does not truly fit the traditional model of higher education. Now, the traditional model of higher education is being challenged and this creates an opportunity for engineering and construction management education to introduce a model that connects the needs of the marketplace to the education provided to the students. This paper examines one construction management program's approach to industry engagement throughout the program in order to increase the quality of education provided to the students. It highlights a cooperative partnership model between the academic program and the construction industry that goes beyond the limits of the traditional Industry Advisory Board of most engineering and construction programs. The results have been impressive for the program, the students, and the industry. The program has been able to stabilize its funding, improve the quality of the education for the students, and make a difference in the lives of those in need in the community. Students have received an excellent education with real-world applications not only on topics required by accreditation but in areas well beyond. Industry partners are hiring jobready graduates who are poised to become the future leaders of the construction industry. [ABSTRACT FROM AUTHOR]