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In this article, we present a study on teachers’ perceptions about Artificial Intelligence (AI) as a tool to support teaching in Estonian K-12 education. Estonia is promoting technological innovation in education. According to the Index of Readiness for Digital Lifelong Learning (IRDLL), Estonia was ranked first among 27 European countries. In this context, our goal was to explore teachers’ perceptions about cutting-edge technologies (in this case, AI) and to contextualize our results in the scope of Fairness, Accountability, Transparency and Ethics (FATE). We carried out a survey with 140 Estonian K-12 teachers and we asked them about their understanding and concerns regarding the use of AI in education and the challenges they face. The analysis of the survey responses suggests that teachers have limited knowledge about AI and how it could support them in practice. Nonetheless, they perceive it as an opportunity for education. The results indicate that teachers need support in order to be efficient and effective in their work practice; we envision that AI can be used to provide this support. Furthermore, we identified challenges that relate to the socio-cultural context of the study: for example, teachers perceived AI as a tool to support them in accessing, adapting and using multilingual content. To conclude, we discuss the findings of this work in relation to ethical AI, and elaborate on the implications and future aspects of this work in the context of FATE and participatory design of learning environments.

Background Inquiry-based learning is widely applied in science education; however, so far, the outcomes of learning process have been systematically assessed mainly at the secondary school level. For primary school students, there is no valid instrument for assessing the outcomes of their science inquiry. The aim of the current study was to develop a test for assessing science learning outcomes (analytical skills, planning skills, interpretation skills, and science knowledge) related to the five phases of inquiry-based learning (Orientation, Conceptualization, Investigation, Conclusion, and Discussion) at primary education level (ISCED 1). Results A set of contextualized science tasks was created to assess each of the learning outcomes at three levels. The Science Inquiry Test for Primary Education (SIT-PE test) was developed through several phases, including pilot studies with large groups of fourth-grade students (10 to 11 years of age). The 1 PL Item Response Theory model was used to analyze the quality of the test and items based on the test’s reliability score, item difficulty measure, infit and outfit indices, estimation of item discrimination, item-scale correlation, and the quality of the scoring key. The final test, consisting of 24 items, was used with a sample of 1868 students. The analysis showed the SIT-PE test to be of good quality on test level and item level and to also have good predictive validity. Confirmatory factor analysis revealed that the correlated factors model and second-order factor model of the science learning outcomes both had a good fit to data collected with the SIT-PE test. Confirmatory factor analysis confirmed the multidimensionality of science learning outcomes and validated four dimensions of the model: analytical skills, planning skills, interpretation skills, and science knowledge. Conclusions In conclusion, the SIT-PE test could be further used for assessing students’ inquiry competence in primary education. However, it could be even further improved in several ways and this study provides guidelines on how to do that. In addition, the SIT-PE provides test developers with information on how to design derivations of the SIT-PE test for assessing particular science inquiry outcomes or the same outcomes in older age groups as well.

In this paper, we focus on the professional agency of student teachers in the initial teacher education context. Based on the ecological model of teacher agency, a questionnaire was developed for a...

Designing and implementing online or digital learning material is a demanding task for teachers. This is even more the case when this material is used for more engaged forms of learning, such as inquiry learning. In this article, we give an informed account of Go-Lab, an ecosystem that supports teachers in creating Inquiry Learning Spaces (ILSs). These ILSs are built around STEM–related online laboratories. Within the Go-Lab ecosystem, teachers can combine these online laboratories with multimedia material and learning apps, which are small applications that support learners in their inquiry learning process. The Go-Lab ecosystem offers teachers ready–made structures, such as a standard inquiry cycle, alternative scenarios or complete ILSs that can be used as they are, but it also allows teachers to configure these structures to create personalized ILSs. For this article, we analyzed data on the design process and structure of 2414 ILSs that were (co)created by teachers and that our usage data suggest have been used in classrooms. Our data show that teachers prefer to start their design from empty templates instead of more domain–related elements, that the makeup of the design team (a single teacher, a group of collaborating teachers, or a mix of teachers and project members) influences key design process characteristics such as time spent designing the ILS and number of actions involved, that the characteristics of the resulting ILSs also depend on the type of design team and that ILSs that are openly shared (i.e., published in a public repository) have different characteristics than those that are kept private.

Educational games have been increasingly used to improve students’ computational thinking. However, most existing games have focused on the theoretical knowledge of computational thinking, ignoring the development of computational thinking skills. Moreover, there is a lack of integration of adaptivity into educational computer games for computational thinking, which is crucial to addressing individual needs in developing computational thinking skills. In this study, we present an adaptive educational computer game, called AutoThinking, for developing students’ computational thinking skills in addition to their conceptual knowledge. To evaluate the effects of the game, we conducted an experimental study with 79 elementary school students in Estonia, where the experimental group learned with AutoThinking, while the control group used a traditional technology-enhanced learning approach. Our findings show that learning with the adaptive educational computer game significantly improved students’ computational thinking related to both conceptual knowledge and skills. Moreover, students using the adaptive educational computer game showed a significantly higher level of interest, satisfaction, flow state, and technology acceptance in learning computational thinking. Implications of the findings are also discussed.

Studies show that technology can have a positive influence on student achievement and motivation; however, the use of technology for educational purposes is rather modest. Research has shown teache...

This article draws on the ecological model of teacher agency and elaborates on how teacher agency is achieved, its components and how it could be strengthened. This model highlights professional co...

The main aim of the present study is to assess whether the open learner model (OLM) is capable of promoting students' active thinking by enhancing their self‐regulation in online higher education learning environments. To this aim, we systematically reviewed the literature of the last three decades and found 67 articles, of which only a sample of 15 were considered. Based on the findings, we performed a narrative analysis of the studies concerning technological features of OLMs that cater to the three main aspects concerning self‐regulated learning, namely, cognition, metacognition and motivation. Our analysis of the literature confirmed that these three aspects are all subject to some measure of influence. In mutually interacting, these three components support learners to reach a better understanding of their learning process. Specifically, it seems that mostly all three type of OLMs, inspectable, negotiable, and co‐operative, with simple and complex graphical presentation of their learner models and capacity to colour‐code and compare—alike appear optimal for augmenting cognition, metacognition, and motivation. They seemingly do so through offering a wealth of techniques pertaining to knowledge, difficulties, and misconception visualization. The results presented suggest that OLMs have a positive impact on learners' active thinking regarding their learning process. Practitioner NotesWhat is already known about this topic Several educational environments have been enhanced with open learner models (OLMs) with the aim of supporting learners.OLM seems to be a potential avenue for improving higher education by supporting learners' active thinking about their learning process by enhancing self‐regulated learning.Despite growing interest in OLMs, there has yet to be any effort to systematically review current research studies investigating their potential to promote self‐regulated learning.What this paper adds All type of OLMs, with their varied visualization features, to some extent are useful for promoting cognitive, metacognitive, and motivational components of self‐regulated learning.In mutually interacting, the three components of self‐regulated learning support learners to reach a better understanding of their learning process, and thereby promoting active thinking.Implications for practice and/or policy We suggest that practitioners must first grasp the possibilities for the cultivation of self‐regulated learning contained in the particular features of each OLM, and then add this insight to their own expertise in order to best integrate them for supporting students' active thinking.While a number of specific features of OLMs seem pertinent to cultivating one particular element of self‐regulated learning, there remains the chance that, through the interaction of cognitive, metacognitive, and motivational tactics, these features could in fact make a more holistic and general contribution. This supports learners to move from active‐in‐behaviour to active‐in‐thinking activities in digital learning environments. [ABSTRACT FROM AUTHOR] uracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The emergency caused by COVID-19 and the transition to distance learning has made teachers face novel decision-making situations. As the teachers&rsquo, pedagogical decisions have an impact on the students&rsquo, learning experience, the aim of this study was to describe and explain what influenced the teachers&rsquo, teaching-related decisions and how these decisions were reflected in the teaching process during distance learning. The study was based on semi-structured interviews with 16 Estonian basic school science teachers. The data were analyzed using qualitative thematic analysis. The results show that teachers&rsquo, teaching-related decisions were influenced by factors that were related to the existence of digital tools as well as to the ability to use them purposefully in the home settings of teachers and students. Teachers&rsquo, teaching decisions were mostly motivated by short-term goals, such as maintaining students&rsquo, social interaction and supporting student motivation. The desire of teachers to keep students&rsquo, and teachers&rsquo, own workload affordable was also considered as a factor influencing teachers&rsquo, teaching-related decisions. According to the interviews, the switch of focus to workload and well-being and valuing socialization and student motivation over subject matter competences seems to be unique for this new situation.

While the Open Learner Model (OLM) is often mentioned to be an educational tool supporting the learning process (chiefly, activities such as planning, self-monitoring, and reflection), there is a need for theorising OLMs as an educational tool. More specifically, this means 1) to theorise what it is educationally meaningful; 2) see how the different characteristics of the tool (e.g. features, types, etc.) mediate the learning process in the light of theory deployed; and 3) empirically determine the conditions under which such mediation is educationally successful. As a case in point, we performed a literature review to investigate how studies using OLMs have deployed self-regulated learning. The results show that the theorisation of OLMs as an educational tool remained rather fragmented and occasional.

Low retention rates in higher education Information Technology (IT) studies have led to an unmet demand for IT specialists. Therefore, universities need to apply interventions to increase retention rates and provide the labor market with more IT graduates. However, students with different characteristics may need different types of interventions. The current study applies a person-oriented approach and identifies the profiles of first-year IT students in order to design group-specific support. Tinto's [13, 14] integration model was used as a framework to analyze questionnaire data from 509 first-year IT students in Estonia. The students’ response profiles were distinguished through latent profile analysis, and the students were divided into four profiles based on their responses to questions about academic integration, professional integration, and graduation-related self-efficacy. The difference in academic integration was smaller among the profiles than the difference in professional integration. Knowing these profiles helps universities to design interventions for each student group and apply the interventions to increase the number of IT graduates.

A significant amount of research has indicated that students&rsquo, procrastination tendencies are an important factor influencing the performance of students in online learning. It is, therefore, vital for educators to be aware of the presence of such behavior trends as students with lower procrastination tendencies usually achieve better than those with higher procrastination. In the present study, we propose a novel algorithm&mdash, using student&rsquo, s assignment submission behavior&mdash, to predict the performance of students with learning difficulties through procrastination behavior (called PPP). Unlike many existing works, PPP not only considers late or non-submissions, but also investigates students&rsquo, behavioral patterns before the due date of assignments. PPP firstly builds feature vectors representing the submission behavior of students for each assignment, then applies a clustering method to the feature vectors for labelling students as a procrastinator, procrastination candidate, or non-procrastinator, and finally employs and compares several classification methods to best classify students. To evaluate the effectiveness of PPP, we use a course including 242 students from the University of Tartu in Estonia. The results reveal that PPP could successfully predict students&rsquo, performance through their procrastination behaviors with an accuracy of 96%. Linear support vector machine appears to be the best classifier among others in terms of continuous features, and neural network in categorical features, where categorical features tend to perform slightly better than continuous. Finally, we found that the predictive power of all classification methods is lowered by an increment in class numbers formed by clustering.

This study investigated students’ collaborative inquiry learning with 5th grade (N = 58, Mage = 11.3 years) and 6th grade (N = 74, Mage = 12.4 years) participants. Students were divided into two- and four-person groups to study whether group size affects their learning with asymmetric collaborative simulations. They worked in online digital learning spaces using tablet computers and communicated face-to-face. The Collaborative Rate of Photosynthesis Lab from the Go-Lab portal (golabz.eu) was used to establish the condition of asymmetric collaboration, and tasks related to it were developed to assess students’ inquiry. To assess students’ collaboration, we used an adapted self-assessed collaboration skills instrument to measure three dimensions: contribution, interaction with others and team learning. The results show that collaboration did not statistically significantly differ depending on group size in the 5th grade, but did in the 6th grade, with 2-person groups reporting better collaboration. Regarding students’ inquiry, analysis of performance on the asymmetric collaborative tasks showed that there were no statistically significant differences between groups in either grade. However, the inquiry task scores were generally low (28% and 40% for 5th and 6th graders respectively), indicating that asymmetric collaborative inquiry is challenging for students in these grades.

School effectiveness research (SER) and bi/multilingual education research have been largely developed as separate research paradigms. Hence, SER research does not facilitate clear conclusions on bi/multilingual (the term ‘multilingual’ is used henceforth) education and its effectiveness. Despite the intensification of multilingual education research over the last four decades, only a few authors and studies have focused on offering a compact overview of what factors need to be in place for the programs to be effective. These works are neither recent nor systematic. In this article, we aim to contribute to this research gap by systematically reviewing the research evidence on specific factors explaining multilingual student success in multilingual education programs. The findings of this systematic literature review integrate the current evidence regarding the critical factors conducive to student success in multilingual education. The results reveal that the reviewed studies mostly discussed school level factors and only occasionally talked about state/regional or individual level factors. We also underscore the critical role of leadership in making multilingual education successful. The implications of this review are twofold: by using a conceptual framework to discuss the success factors, the interdependence of the variables shaping multilingual education is highlighted, while the results collect the latest evidence for decision makers in multilingual education.

Several studies have reported that adaptivity and personalization in educational computer games facilitate reaching their full educational potential. However, there is little effort to develop adaptive educational computer games for promoting students' computational thinking (CT). In this study, an adaptive computer game is introduced, called AutoThinking, that not only promotes both CT skills and conceptual knowledge, but also provides adaptivity in both game-play and learning processes. To evaluate the possible effects of the game, an experimental study was carried out with 79 students in an elementary school in Estonia. AutoThinking and a conventional technology-enhanced learning approach were used for teaching CT to the experimental and control group, respectively. Our results reveal that AutoThinking improved students’ CT skills and conceptual knowledge better than the conventional approach. It was also found that students with a low and high level of prior knowledge made higher improvement in knowledge gain using the adaptive game compared to the traditional approach, especially those students with lower prior knowledge. Finally, our findings show that the adaptive game could also improve students' learning attitude toward CT better than the conventional approach, especially those students with higher prior learning attitudes.

Despite the high competition for places to study curricula related to information technology (IT) at the higher education level in Estonia, a large number of IT students drop out. Therefore, it is important to explore what influences students to start studying IT and what influences them to persist with their degree program. In this study, data were collected from 301 IT students in Estonia. The students completed a questionnaire at the beginning of their studies and after their first semester. Five factors influencing students' motivation were identified from analysis of these questionnaires. Three of these factors were the same at the beginning of and during studies: previous personal contact with IT, the reputation of the IT field, and development (including self-development and IT field development). A fourth factor related to a desire to continue previous IT studies was found to influence students' motivation only when entering university. A fifth, i.e., learning environment, factor was found to influence motivation only during studies. The outcomes of this study are important for developing new interventions to increase students' interest in IT, their enrollment in IT studies, and their retention.

The open learner model (OLM) represents the knowledge or skill levels of learners in various ways, encouraging learners to actively participate in thinking about and crafting their own learning. Despite the important roles that OLMs play in higher education to support the learning process and self-regulated learning (SRL) in particular, there are few studies systematically reviewing OLM technology in higher education, and investigating their potential to foster self-regulated learning. Therefore, we carried out a systematic review of a 30-year sample of OLM studies in higher education and identified 64 articles that study the use of OLMs in supporting SRL. Our findings show that OLMs have been mainly used to support learners' cognition and a bit less metacognition and motivation; however, emotional support has been rarely provided. The most supported ones are Appraisal and Performance phases; Preparation of learning is enhanced by OLMs not so often. Although learners can edit or negotiate with their learning model in advanced ways, a simple inspectable OLM is more preferred. Reliance on unobservable nodes is less favored in modeling techniques in OLMs because such methods are highly dependent on expert authoring, thereby time-intensive and costly. Comparison and color-coding are two most-used features in OLMs, where the comparison feature is often used for enhancing learners’ engagement and motivation.

The general goals of education have changed in the 21st century. The contemporary learning approach aims at achieving better self-fulfillment, openness and lifelong learning opportunities for every learner. This presents new demands on technologies. Technological advancements are often ahead of their use in educational settings, but nowadays we can also see that the contemporary learning approach sets unmet demands to technology developers. This paper introduces the objectives of the contemporary learning approach and discusses how 11 existing advanced technologies could help achieve the objectives of the contemporary learning approach. The review shows that educational technologies are mainly designed to improve subject knowledge and skills and can be quite often used to support collaboration and self-regulation as well. However, learning skills and especially subjective well-being are less in focus.

Modern teaching methods, including the need to use information technology in teaching, are receiving increasingly more attention in higher education pedagogy. The purpose of this paper is to provide an overview of the technology mentoring programme that was launched in the University of Tartu and to categorise the reasons why 15 university teachers who specialise in the field of education decided to take part in the technology mentoring programme, describe their expectations of the programme and describe their current teaching practices with regard to employing ICT at the start of the mentoring programme. Results indicate that the main reason for joining the programme was the teachers' wish to make learning more interesting for both themselves and their students. By joining the programme, university teachers hoped to gain more knowledge of various ways to use technology in teaching, thereby supporting students in their learning efforts. The opportunity to have systematic discussions about teaching-related topics with other participants of the technology mentoring programme was also considered an asset. At the start of the programme, the university teachers described their own experience of using ICT mainly in connection with information retrieval, content creation and communication.

We review interactive computer-based tasks from several large-scale (n > 20,000) educational assessments in order to better understand the advantages of these assessment items and how they can inform the development of computer-based items to assess students’ digital competence. Digital competence is considered to be an essential competence in today’s knowledge-based society and has been described in the DigComp framework as consisting of 21 individual competences grouped under 5 areas: information and data literacy, communication and collaboration, digital content-creation, safety and problem-solving. In the present paper we examine interactive computer-based tasks from three large-scale assessments and conclude by mapping constructs from these assessments to the DigComp framework. A look at this mapping provides an initial view of which aspects of the DigComp framework require the most attention in terms of developing interactive computer-based items for a potential instrument to assess students’ digital competence.

Despite the use of mobile devices becoming more ubiquitous, and the possibilities they offer for learning becoming more recognized, research shows that mobile devices are not always used to their fullest potential. Previous studies have found that attitudes towards technology can influence whether, and in what way, mobile devices are used. At present, there have been few studies focusing on samples of basic school students and mobile device use. It was our aim, therefore, to test whether the widely used theoretical UTAUT model could also be applied to a sample of basic school students, or whether some changes would be required before it could be used for a study of attitudes towards mobile devices among basic education students. 3521 Estonian basic school students from 6th (n = 2673) and 9th (n = 848) grades participated in the study. From the results 4 attitude factors could be distinguished. These included: Self-efficacy, Social Influence, Anxiety and Performance Enjoyment. The attitudes towards mobile devices in learning explained approximately 43% of the variance of student’s Behavioural Intention to use mobile devices, while Performance Enjoyment played a mediating role on the influence of Self-efficacy. Behavioural Intention explained 2% of the variance in the use of mobile devices for learning. The results suggest that some changes should be considered when researching students’ attitudes towards mobile devices in basic education.

In this study we introduce a guided reflection procedure that aims to support student teachers in developing knowledge based on their practical experiences and by linking this with theoretical knowledge. Student teachers (n=22) with varying prior teaching experiences carried out the guided reflection procedure at a university in Estonia. In an empirical study we focused on student teachers’ experiences and feedback on the guided reflection procedure. Data was collected with interviews and group interviews, and analysed employing a thematic analysis method. The findings showed that the perceived value of the reflection procedure is related to student teachers’ prior pedagogical experiences.

Reflection is a cognitive process that can help students understand and learn from their learning experiences. This implies thinking back about the course of learning processes in order to enable better behaviour and actions in the future. Reflection is more efficient if it is supported by technological tools. These tools offer the ability to present detailed information about learning processes (e.g., use of time during a specific learning process) and the ability to provide guidance, for example in the form of questions that support reflection. In this paper we present the results of a study carried out with 9th grade students (mean age 15.0 years, n=59) to clarify the role of a Reflection Tool to support students’ reflection. The Reflection Tool in this study is a web-based application that was tailored for a chemistry-based Inquiry Learning Space (ILS) called “What does pH measure?”. The ILS and Reflection Tool were developed as part of the EU funded project called Go-Lab (see www.go-labproject. eu). Students were divided into two conditions. In experimental condition the Reflection Tool was used and in the control condition it was not. Furthermore, two types of devices were used to implement the Reflection Tool: tablets and personal computers. Assessment of the Reflection Tool was based on coding the response to open-ended questions that support reflection. Two aspects were assessed in students’ reflections: content (technical, situational and sensitising) and reflection level (description, justification, critique, dialogue and transfer). A qualitative analysis and a non-parametric Mann-Whitney U-test were used to detect to what extent the Reflection Tool helps identify students’ reflection content and levels. Although, there was no statistically significant difference in favour of the Reflection Tool, the results still showed that the Reflection Tool enabled to identify students’ reflection content and levels. In this paper we discuss the possible interpretations of these results.

In this study we aimed to identify the relation between students’ reflection levels and their inquiry learning outcomes (i.e. their formulated conclusions) after conducting a complete inquiry cycle in an online Go-Lab Inquiry Learning Space (ILS). We expected that students exhibiting a higher reflection level would be more experienced in formulating higher quality conclusions than students at a lower reflection level. Forty-three students from the 9th grade with an average age of 15 years from two Estonian public schools participated in this study. During the interventions students worked with a chemistry-based ILS called “What does pH measure?” Students were given a pre-defined problem to be solved by following an inquiry cycle. In each phase students had tasks to perform which led to concrete learning outcomes. The students used specific application called Conclusion Tool to state their conclusions and used Reflection Tool to answer two open-ended reflective questions to reflect on their study process. The results suggest that students who reflect at a higher reflection level are more successful in formulating higher quality inquiry outcomes such as hypotheses, observations and conclusions. Therefore it seems that reflection should be part of the learning process in order to support students to achieve higher quality inquiry learning outcomes.

The ability to use digital technologies to live, work and learn in today’s knowledge-based society is considered to be an essential competence. In schools, digital technologies such as smart devices offer new possibilities to improve student learning, but research is still needed to explain how to effectively apply them. In this paper we developed an instrument to investigate the digital competences of students based on constructs from the DIGCOMP framework and in the contexts of learning science and mathematics in school and outside of school. Pilot testing results of 173 students from the 6th and 9th grades (M = 12.7 and 15.7 years of age, respectively) were analyzed to remove unnecessary items from the instrument. The pilot study also showed preliminary smart device usage patterns that require confirmation by a large-scale study. Digitally competent use of smart devices may help facilitate widespread use of computer-based resources in science education.

Science Created by You (SCY) is a project on learning in science and technology domains. SCY uses a pedagogical approach that centres around products, called 'emerging learning objects' (ELOs) that are created by students. Students work individually and collaboratively in SCY-Lab (the general SCY learning environment) on 'missions' that are guided by socio-scientific questions (for example 'How can we design a CO2-friendly house?'). Fulfilling SCY missions requires a combination of knowledge from different content areas (eg, physics, mathematics, biology, as well as social sciences). While on a SCY mission, students perform several types of learning activities that can be characterised as productive processes (experiment, game, share, explain, design, etc), they encounter multiple resources, collaborate with varying coalitions of peers and use changing constellations of tools and scaffolds. The configuration of SCY-Lab is adaptive to the actual learning situation and may provide advice to students on appropriate learning activities, resources, tools and scaffolds, or peer students who can support the learning process. The SCY project aims at students between 12 and 18 years old. In the course of the project, a total of four SCY missions will be developed, of which one is currently available. [ABSTRACT FROM AUTHOR]

Designing a computer-supported learning scenario involving a constructivist approach of learning lays on a paradox. On the one hand, learning flows must be precisely described - including role distribution, required resources, tools, and scaffolds - to be realized in computer-supported environments. On the other hand, a fine-grained formalization of learning flows diverges from the constructivist notion of learning that learners are responsible for their knowledge (co-)construction. This paper draws upon the fundaments of a new concept so called ldquolearning activity spacerdquo (LAS) aiming at realizing some necessary flexibility when designing learning scenarios. LAS is the basis of a graphical scenario modeling language intelligible for non-computer scientists but still rich enough in detail to describe a large set of computer-supported learning scenarios.