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• A pedagogically planned and scaffolding scenario-based design teaching process established novice preschool programmers with overall programming skills in a tangible programming context. • Two types of debugging knowledge emerged: i) syntactic and ii) semantic. The second type was revealed to be more complex for children to develop, mainly when two bugs occurred within the same program. • Half of the children presented complete and functional programs. Many children applied effective debugging strategies from their coding experience, although they were not involved in activities focused on debugging. • A dominant debug strategy is composing a 'new program'. Two more strategies emerged: verbal and 'pseudocode'. The present study investigates the debugging process of 526 children in preschool (4–6 aged) when programming a tangible robot. When a child is involved in programming, it is needed to identify and correct errors, or in other words, debug a program. Debugging is a high-level thinking skill and is an essential component closely related to developing Computational Thinking in early childhood education. Though the debugging process is a cognitive function in programming investigated by many researchers in recent decades, most studies are conducted either in primary, secondary education, or higher education concerning beginners or experts in programming. Very few reviews, and some focus on preschool education. Our study set out the following objectives: 1) How do children identify the existence of error and locate it? 2) What types of errors emerge when coding? 3) What type of error is complex for novice programmers? 4) What strategies are developed by novice programmers to debug effectively? and 5) What types of knowledge do novice programmers construct by debugging the tangible robot Bee-Bot? The study follows an iterative model of a design-based research approach. It uses multiple case studies to collect qualitative and quantitative data. The programming intervention was implemented by 30 educators in their classrooms and was based on a scenario-based teaching design. The debugging process was analysed using Klahr & Craven's framework (1988): 1) test and evaluate program, 2) identify bug, 3) represent program, 4) locate bug and 5) correct bug. The main finding is the construction and development of syntactic and semantic knowledge. [ABSTRACT FROM AUTHOR]

Over the past decade research has recognised the learning potential of massively multiplayer online games (MMOGs). MMOGs can be used by the technology-enhanced learning research community to study and identify good educational practices that may inspire engaging, creative and motivating approaches for education and learning. To this end, in this research paper, we aim to explore the learning outcomes and processes emerging in the environment of MMOGs by initially studying the relevant perceptions of the players. Based on a theoretical framework referring to the cognitive, the social, and the affective aspects of a technology-supported learning environment, and through a mixed-method research and the analysis of qualitative data from 22 individual and group interviews, and quantitative data from a wider survey (minimum N = 221), we map and examine the cognitive, the skill-based, the social, and the affective potential impact of MMOGs. More specifically this study presents the perceptions of players on the learning impact of MMOGs, the potential transfer of skills to other domains, the learning practices they employ, and elements of the design of the environment that may present positive conditions for learning. We attempt to contribute to the research field and also provide insights for the design of technology-enhanced learning environments, by examining and mapping elements of MMOGs from the perspective of the design of an effective learning environment and based on empirical data. [ABSTRACT FROM AUTHOR]

Although there is strong evidence that massively multiplayer online games (MMOGs) constitute environments of social interactions and effective learning, we currently lack the tools for investigating the effectiveness of the social networks emerging as well as the cognitive aspects and knowledge acquisition such environments involve. Within this context, we present a conceptual framework for the investigation of the collaborative problem-solving processes emerging in such environments and we apply it in the investigation of a number of MMOGs through interviews and virtual ethnography. Our findings suggest the balanced convergence of multiple factors, such as the mechanics of the game, the design of the tasks, the collaboration and competition affordances and the content of the game, for the constitution of an effective environment for collaborative learning. [ABSTRACT FROM AUTHOR]

Abstract: This study aims at highlighting the collaborative activity of two high school students (age 14) in the cases of modeling the complex biological process of plant growth with two different tools: the ‘paper & pencil’ concept mapping technique and the computer-supported educational environment ‘ModelsCreator’. Students’ shared activity in both cases is carried out in the presence of a facilitator providing technical as well as cognitive support when necessary. The objective of the study is to highlight the ways in which the collaborating students are engaged in the plant growth modeling activity in the two cases and also identify the activity’s similar and different aspects in each one. Our analysis is carried out on two complementary axes, the first of which concerns the process of collaboratively creating a plant growth model with each different tool, while the second has to do with the students’ conceptualizations of the biological aspect of the modeling task in each case. A two-level analytic tool for the modeling process has been derived within the theoretical framework of ‘activity theory’ on the basis of the OCAF scheme for basic modeling operations and the scheme of Stratford et al. [Stratford, S. J., Krajcik, J., & Soloway, E. (1998). Secondary students’ dynamic modeling processes: analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education and Technology, 7(3), 215–234.] for higher-order modeling actions. According to our results, four major modeling actions (analysis, synthesis, testing-interpreting, technical and cognitive support) performed through a plethora of modeling operations define the steps of the modeling process in both cases, while specific qualitative differences can be actually identified. Finally, the students’ conceptualizations of the biological aspect of the modeling task in the two-case activity is analyzed in regard with their capability of shifting reasoning between macro- and micro-levels, while educational implications are also discussed. [Copyright &y& Elsevier]

This paper highlights specific aspects of high-school students’ reasoning while coping with a modeling task of plant growth in a computer-supported educational environment. It is particularly concerned with the modeling levels (‘macro-phenomenological’ and ‘micro-conceptual’ level) activated by peers while exploring plant growth and with their ability to shift between or within these levels. The focus is on the types of reasoning developed in the modeling process, as well as on the reasoning coherence around the central concept of plant growth. The findings of the study show that a significant proportion of the 18 participating dyads perform modeling on both levels, while their ability to shift between them as well as between the various elements of the ‘micro-conceptual’ level is rather constrained. Furthermore, the reasoning types identified in peers’ modeling process are ‘convergent’, ‘serial’, ‘linked’ and ‘convergent attached’, with the first type being the most frequent. Finally, a significant part of the participating dyads display a satisfactory degree of reasoning ‘coherence’, performing their task committed to the main objective of exploring plant growth. Teaching implications of the findings are also discussed. [ABSTRACT FROM AUTHOR]

This paper examines the effect of heterogeneous resources, available to students, during computer-supported collaborative problem solving. A study of collaborative modeling has been conducted in the frame of an authentic educational activity in a secondary school. The students involved were provided with sets of primitive resources of varying degrees of heterogeneity to be used during synchronous computer-mediated modeling activities. Analysis of students'' peer interaction and of the produced solutions revealed that, contrary to our expectations, the group with heterogeneous resources produced solutions of similar quality to those of the reference group, although they were more active, they exchanged more messages, they were involved in deeper discussions and collaborated more for building the constituent parts of the solution. [Copyright &y& Elsevier]

Recent research emphasizes the importance of Artificial Intelligence applications as supporting tools for students in higher education. Simultaneously, an intensive exchange of views has started in the public debate in the international educational community. However, for a more proper use of these applications, it is necessary to investigate the factors that explain their intention and actual use in the future. With the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, this work analyses the factors influencing students' use and intention to use Artificial Intelligence technology. For this purpose, a sample of 197 Greek students at the School of Humanities and Social Sciences from the University of Patras participated in a survey. The findings highlight that expected performance, habit, and enjoyment of these Artificial Intelligence applications are key determinants influencing teachers' intentions to use them. Moreover, behavioural intention, habit, and facilitating conditions explain the usage of these Artificial Intelligence applications. This study did not reveal any moderating effects. The limitations, practical implications, and proposed directions for future research based on these results are discussed. [ABSTRACT FROM AUTHOR]

Although reflective practice is now a key competency in many teacher training programs, the theoretical grounding remains problematic and the empirical approaches diverse. With the aim of advancing our understanding of the limitations of reflective practice in initial teacher training, this article draws a critical portrait of reflective practice in terms of theory, practice and methodology based on a review of the literature. We conclude by underscoring the need for a shared terminology and definition for reflective practice in initial training programs; currently, the lack of a clear concept hinders its operationalization in teacher training and its development in empirical research. [ABSTRACT FROM PUBLISHER]

Abstract: Database design and use has educational interest for utilitarian and learning reasons. Database technology has significant economic impact and the demand for database design cannot be covered by the existent educated experts. Furthermore, the database management systems available at schools could be used for the design and implementation of high quality learning activities. Databases are general purpose modeling environments that enable problem solving using conceptual frameworks closer to the solver and the problem than the machine architecture. Databases design introduction in the curricula of secondary education programs raises educational research questions. Research questions concern the didactics of the subject as well as the value of database design based learning activities. In this paper, we present some of the more significant findings of an action research concerning the database design in secondary education. Research questions concern the ideas of students about databases and their difficulties during database design. Data, collected using a variety of research activities, are analyzed and discussed and teaching strategies are proposed. [Copyright &y& Elsevier]

During the last decade an increased interest has been observed on computer-supported collaborative problem solving. This relatively new area of research requires new methodological approaches of interaction and problem solving analysis. Usually analysis of collaborative problem solving situations is done through discourse analysis or interaction analysis, where in the center of attention are the actors involved (students, tutors etc.). An alternative framework, called “Object-oriented Collaboration Analysis Framework (OCAF)” is presented here, according to which the objects of the collaboratively developed solution become the center of attention and are studied as entities that carry their own history. This approach produces a reversed view of the process, according to which the solution is made of structural components that are ‘owned’ by actors who have contributed in various degrees to their development. OCAF provides both qualitative and quantitative measures of collaboration. It is shown that this framework can be applied effectively both in synchronous computer supported collaborative environments of distance groups and in face-to-face collaborative activities. [Copyright &y& Elsevier]

During the last years, development of open learning environments that support effectively their users has been a challenge for the research community of educational technologies. The open interactive nature of these environments results in users experiencing difficulties in coping with the plethora of available functions, especially during their initial efforts to use the system. In addition, -from the tutors' perspective- the problem solving strategies of the students are often particularly difficult to identify. In this paper, we argue that such problems could be tackled using machine learning techniques such as Bayesian Networks. We show how we can take advantage of log files obtained during field studies to build an adaptive help system providing the most useful support to the student, according to the state of interaction. On the other hand, we attempt to support the tutor, by automating the process of diagnosing students' problem solving strategies using Bayesian Networks. The presented approaches are discussed through examples of two prototypes that have been developed and corresponding evaluation studies. These studies have shown that the proposed approach can effectively support the tasks of students and tutors in such open learning environments. [ABSTRACT FROM AUTHOR]