A Framework and an Instructional Design Model for the Development of Students\u27 Computational and Algorithmic Thinking

The authors herein, describe their efforts towards designing technology-enhanced instruction for teaching Computational and Algorithmic Thinking. This study examined students’ development of Computational and Algorithmic Thinking, by utilizing the framework of Technological Pedagogical Content Knowledge and the instructional design model of Technology Mapping. Different technological tools were used for both groups of participants; the experimental and the control group. In particular, the experimental group used educational robotics and the control group used a 3D interactive programming environment. Both groups were 8th graders coming from different secondary education schools in Cyprus. A pre-post test research design was adopted in each classroom intervention. To check whether the interventions facilitated students’ development and understanding of Computational and Algorithmic Thinking concepts and competencies, an analysis of covariance (ANCOVA) was then conducted. According to the results, the framework of Technological Pedagogical Content Knowledge and the approach of Technology Mapping, which guided the design of the instructional intervention were effective in terms of fostering students’ development and understanding of Computational and Algorithmic Thinking competencies and concepts, respectively

Measuring the Internet Skills of Gen Z Students in Higher Education: Validation of the Internet Skills Scale in University Settings

[EN] Internet technologies have infiltrated higher education institutions around the world. At the same time, the latest generation of students, the so-called Generation Z (Gen Z), are entering higher education. Gen Z is the first generation born in an Internet-connected world, and digital devices are a seamless part of its life. As a result, Gen Z students have already been engaged with informal digital learning via internet-based technologies outside of formalized education settings. However, previous research has shown that their engagement with these technologies is limited and might not sufficiently cover the knowledge and skills needed to perform internet activities effectively in higher education. Additionally, their familiarity with digital devices and tools varies. Consequently, there is a need for higher education institutions to close the skills gap by applying assessment processes that will assist them in forming policies and training resources for undergraduate students. To achieve the above, research efforts need to focus on developing theoretically informed and valid instruments that measure internet skills. This study has contributed to the validation of a self-assessment questionnaire, the Internet Skills Scale, that can be used in university settings. The questionnaire measures five types of internet skills: operational, information-navigation, social, creative, and critical. The results presented herein provide directions for future research in the field.Miliou, O.; Angeli, C. (2021). Measuring the Internet Skills of Gen Z Students in Higher Education: Validation of the Internet Skills Scale in University Settings. En 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. 1359-1368. https://doi.org/10.4995/HEAd21.2021.13070OCS1359136

Field dependence–independence and instructional-design effects on learners’ performance with a computer-modeling tool

Angeli, C., Valanides, N., & Kirschner, P. A. (2009). Field dependence–independence and instructional-design effects on learners’ performance with a computer-modeling tool. Computers in Human Behavior, 25, 1355–1366.The study investigated the extent to which two types of instructional materials and learner field dependence– independence affected learners’ cognitive load, time spent on task, and problem-solving performance in a complex system with a computer-modeling tool. One hundred and one primary student teachers were initially categorized into field dependent, field mixed, and field-independent learners based on their performance on the Hidden Figures Test, and were then randomly assigned to two experimental conditions. One group received a static diagram and a textual description in a split format, and the second group received the same static diagram and textual description in an integrated format. MANOVA revealed that the split-format materials contributed to higher cognitive load, higher time spent on task, and lower problem-solving performance than the integrated-format materials. There was also an interaction effect, only in terms of students’ problem-solving performance, between field dependence– independence and instructional materials, indicating that the facilitating effect of the integrated-format materials was restricted to the field-independent learners. Conclusions are drawn in terms of how the well-documented split-attention effect manifests itself irrespective of students’ field dependence-independence. Implications of the effects of reduced extraneous cognitive load on students’ problem-solving performance are also discussed

Investigating the effects of gender and scaffolding in developing preschool children’s computational thinking during problem-solving with Bee-Bots

The research community has embraced computational thinking as an essential skill to develop in school and academic settings. Many researchers argue that computational thinking should be developed in the context of programming and robotic activities in all educational levels of education, starting from early childhood education. However, the factors related to developing computational thinking in preschool education are still under study. Furthermore, not too many empirical investigations provide evidence about the development of computational thinking in young children. The present study examined the effects of scaffolding and gender in developing young children’s sequencing and decomposition skills - two of the five skills that constitute computational thinking. The results indicated statistically significant effects about the type of scaffolding on children’s computational thinking in favor of the children assigned to the experimental groups. Lastly, boys outperformed girls on all occasions, indicating that gender effects exist. The authors conclude that researchers need to design teaching interventions in such a way so they have mathemagenic outcomes for all learners irrespective of gender. Finally, the authors conclude with implications and future research directions

From gatekeeper to proto-online tutor: The role of parents in digital education

This paper presents a cross-national qualitative study examining the role of parents in digital education during the Covid-19 pandemic in five schools in each of four European countries—Cyprus, Ireland, Malta, and Northern Ireland. Unlike previous studies that largely document the unprepared transition to remote teaching during the first lockdown (March-June 2020), this research investigates how parents adapted to new roles, navigated complex circumstances, and maintained changes in their involvement in digital education during the subsequent lockdowns and reopening periods. The study also examines the impact of socio-economic status on parental engagement and the influence of school type on parental embrace of digital education. The findings indicate that while socio-economic status and school type have some impact, other factors such as access to resources, immigrant status, and language barriers play a significant role in parental engagement. Despite differences in educational systems and cultural contexts, similar challenges persisted across the countries. The paper argues for more context-sensitive strategies to enhance parental engagement in digital education

Editorial. Teacher education for effective technology integration

About a decade ago, several researchers used Shulman’s (1986) framework about Pedagogical Content Knowledge (PCK) – a body of knowledge that constitutes a special amalgam of content, pedagogy, learn- ers, and context – as a theoretical basis for developing TPCK or TPACK: a framework for guiding teach- ers’ cognition about technology integration in teaching and learning (Angeli, Valanides, & Christodoulou, 2016). Different models of TPCK/TPACK are proposed in the literature, each with a different focus (on practice, instructional design, context, etc.) and with a different theoretical interpretation about the nature and development of the knowledge that teachers need to have to be able to teach with technology (e.g., Angeli & Valanides, 2005, 2009, 2013; Koehler & Mishra, 2008; Niess, 2005). The two dominant TPCK/ TPACK models in the literature are the integrative model and the transformative model. The integrative model is more closely associated with the term TPACK, and was proposed by Koehler and Mishra (2008). It conceptualizes TPCK as an integrative body of knowledge that is created on the spot by the mere inter- sections between different bodies of knowledge, such as content and pedagogy, content and technology, and pedagogy and technology. The transformative model was proposed by Angeli and Valanides (2005) and, unlike the integrative model, it conceptualizes TPCK as a unique body of knowledge that needs to be ex- plicitly taught by teacher educators. In the transformative model, content, pedagogy, learners, technology, and context are regarded as significant individual contributors to the development of TPCK. While the integrative and transformative models view TPCK as an extension of Shulman’s (1986) PCK, the two models are based on different epistemological stances regarding the nature of TPCK. TPACK is represented in terms of three intersecting circles, one for each distinct knowledge base, namely content, pedagogy and technology (Koehler & Mishra, 2008), while its subcomponents, i.e., technological con- tent knowledge (TCK), technological pedagogical knowledge (TPK) and pedagogical content knowledge (PCK), are also distinctly examined. So far, empirical findings from this line of research are rather discour- aging, because it has proven too difficult to define the boundaries of the different TPACK sub-components (Graham, 2011). Angeli and Valanides’ framework of TPCK is conceptualized in terms of five distinct knowledge bas- es, namely content knowledge, pedagogical knowledge, knowledge of learners, knowledge of educational context, and ICT knowledge (Angeli & Valanides, 2005, 2009). Based on the results of empirical investi- gations, Valanides and Angeli (2008a, 2008b) concluded that TPCK is a distinct body of knowledge that goes beyond mere integration or accumulation of the constituent knowledge bases toward their transforma- tion into something new and unique. For this reason Angeli and Valanides have not adopted the new term TPACK, opting instead to continue using TPCK, because TPACK appears to be more closely associated with the integrative view rather than the transformative view. TPCK as a transformative body of knowl- edge is defined as knowledge about how to transform content and pedagogy with ICT for specific learners in specific contexts and in ways that leverage the added value of ICT (Angeli & Valanides, 2009). Angeli and Valanides (2013) invested extensive research efforts in developing TPCK in the form of instructional design competencies that teachers need to develop in order to be able to teach with technology effectively. A conceptualization of TPCK in terms of design competencies has led to more robust and reliable ways of assessing learners’ TPCK, bypassing measurement difficulties of the nature that researchers who adopted the TPACK framework reported in their studies (Archambault & Barnett, 2010; Cox & Graham, 2009; Graham, 2011). In this direction, research is being carried out to identify TPCK design procedures for initial teacher educa- tion. In teaching, when transferring TPCK to design and methodological practices, there is a need to con- sider a number of factors, especially: the different modes of adopting technologies; the integration of tool affordances, content and pedagogy; the implementation of learning environments; the operationalization of knowledge; and detailed analysis of teaching models and approaches (De Rossi, 2015; Messina & De Rossi, 2015; Messina, De Rossi, Tabone, & Tonegato, 2017; Messina & Tabone, 2011; 2012). In an effort to advance the research into TPCK, this special issue of IJET reports on the latest developments in the field, identifying both gaps and findings that indicate potential for future research directions. [...