Search

Serious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires–postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict knowledge change based on in‐game student interactions. We have tested this approach in a case study for which we have conducted preexperiments–postexperiments with 227 students playing a previously validated serious game on first aid techniques. We collected student interaction data while students played, using a game learning analytics infrastructure and the standard data format Experience API for Serious Games. After data collection, we developed and tested prediction models to determine whether knowledge, given as posttest results, can be accurately predicted. Additionally, we compared models both with and without pretest information to determine the importance of previous knowledge when predicting postgame knowledge. The high accuracy of the obtained prediction models suggests that serious games can be used not only to teach but also to measure knowledge acquisition after playing. This will simplify serious games application for educational settings and especially in the classroom easing teachers' evaluation tasks. Lay Description: What is currently known about the subject matter Serious games are a powerful tool to engage, motivate, and help students learn.Pre‐post experiments are commonly used to measure knowledge acquisition.Game learning analytics can be applied to interaction data from games. What this paper adds We present a two‐step approach combining game learning analytics and data mining to predict players' performance in serious games based on their interactions.The approach is tested in a case study with pre‐post experiments collecting interaction data with 227 students playing a serious game to determine if performance can be accurately predicted.The comparison of prediction models has helped to determine if pretest information is essential.The highly accurate prediction models obtained suggest that games can be used to teach and measure knowledge acquisition after playing. Implications of study findings for practitioners The approach aims to simplify the measurement of players' learning with serious games.It may be generalized at least to similar scenarios (e.g., games for procedural learning or game‐likesimulations) where similar interaction data are feasible.Game mechanics and educational design should define the interaction data to capture.Using an accepted standard tracking profile is a clear recommendation. [ABSTRACT FROM AUTHOR]

Background: The present study analyses the design of programming literacy in the sixth grade of Primary Education, starting from the use of simple activities with visual block‐based programming, through Scratch, and progressively linking difficulty to the use of the Unity engine, and the C# language, with simple activities identical to those created in Scratch. Objectives: This research aims to evaluate future teachers' abilities and attitudes regarding programming and its educational possibilities. We intend to evaluate the viability of a teaching proposal that combines a visual block‐based programming environment and a more advanced one, based on C#. Method: In the settings of two public Spanish universities, we analyse the possibilities in the training of future teachers who are studying for a degree in Primary Education Teaching and a degree in Pedagogy. Based on a test and three scales, descriptive data and statistical inference are detailed through a quasi‐experimental design with a Student's t‐test in the first dimension, and a Wilcoxon test in the second dimension. Results: The participants improved their performance and attitudes towards programming with the intervention of the study in the use of coding. Conclusions: It can be concluded that coding is essential in teacher training, and that a greater presence of programming training in higher education is essential. The benefits are visible in the pedagogical approach of coding related to creativity, innovation, motivation, an active approach and interest, highlighting the fact that the implementation of visual block‐based programming by blocks and engines is feasible in Elementary Education. The training proposal—provided by appropriate progression, selection, and sequencing of content—fosters basic and practical teacher training, and this can be defined as an apt training solution. Lay Description: What is already known about this topic: Visual Programming Language (Scratch) provides benefits in educational contextsEducational Technology in classroom provides motivation and encouragement.Active methods and interactions are interesting and beneficial to elementary school students What this paper adds: Visual programming and game engine are feasible in Elementary Education, detailing significant improvements regarding academic outcomesWe found benefits in this pedagogical approach related to creativity, innovation, motivation, active approach and interest. Implications for practice and/or policy: Due to the benefits and positive results obtained in this research it is recommended to implement Visual Programming LanguageWe recommend the introduction to engine in educational settings in 6th grade in primary education though a cross‐curricular implementation.We recommend to apply an active approach, innovation, and learning computational concepts. [ABSTRACT FROM AUTHOR]

Elaborative feedback (EF) containing explanations on students' responses benefits learning. Computer‐based environments provide learners with EF in different ways, for example, on an immediate question‐by‐question basis or after answering a set of questions. Recent findings also suggest that delaying EF enhances learning. However, it is unclear to what extent different types of delayed‐EF favour students' performance. This study examines whether and how two types of delayed‐EF (question‐based vs. summative) influence students' question‐answering performance and final learning over immediate‐EF. One hundred thirty‐three secondary‐school students read a scientific text and answered 12 multiple‐choice questions in a computer‐based environment. A day later, students completed a final learning test with 20 open‐ended questions. Results showed that neither question‐based delayed EF nor summative delayed EF outperformed immediate EF. However, EF moderated the relationship between students' prior knowledge and their performance outcomes, suggesting that students with higher levels of prior knowledge receiving summative delayed EF benefited more. Lay Description: What is already known about this topic: Elaborative Feedback (EF) containing explanations about the students' responses benefits learning.Computer‐based learning environments can provide students with different types of delayed and immediate EF messages.Results in regard to what type of delayed EF is best for learning are inconclusive.EF effects can vary as a function of individual differences in Prior Knowledge. What this paper adds: The role of delaying EF over immediate EF on both question‐answering and learning outcomes.The effects of summing up EF (summative)in comparison to delivering question‐based EF.The interplay between students' prior knowledge and EF on question‐answering and learning outcomes. Implications for practice and/or policy: Neither question‐based nor summative delayed EF outperformed immediate EF.Students with higher levels of prior knowledge receiving summative delayed EF benefited more.Designers of computer‐based learning environments may provide learners with delayed EF messages.The design of content‐efficient EF cannot be fully understood without considering learners' prior knowledge. [ABSTRACT FROM AUTHOR]

The present study evaluated the effects of web‐based training on Spanish pre‐service and in‐service teacher knowledge and implicit beliefs on learning to write. A sample of pre‐service teachers and in‐service teachers from Mexico, Guatemala, Ecuador, Colombia, and Spain participated in the online course. Findings suggest that teachers may improve their knowledge of transcription skills (i.e., handwriting/typing, spelling), text production, and strategies for composing as necessary components of quality writing instruction. Effects were also found on the teachers' implicit beliefs. Finally, both pre‐service and in‐service teachers positively rated the online course received. Lay Description: What is currently known about the subject: Teaching children how to write demands a high degree of specialization.The benefits of web‐based training to professional development have been well‐documented in the literature.Preparing of pre‐service and in‐service teachers through an online context is limited in the field of writing.Teachers' knowledge, satisfaction, and beliefs have been commonly used as outcome measures to define high‐quality e‐learning instruction. What this paper adds: A Spanish web‐based training was developed to improve professional development in writing instruction.The Trazo web‐based training changed teacher's beliefs about learning to write.Teachers learned more about the essential component of the writing process.Teachers' rating of the training and support website was highly positive. Implications for practitioners: Web‐based training allows teachers to learn at their own pace.Teachers can improve their knowledge from virtually at any geographic location with an Internet connection.The Trazo web‐based training offers research‐based knowledge to Spanish‐speaking teachers. [ABSTRACT FROM AUTHOR]

The Knowledge Society, along with the non‐stop growing technological evolution, entails university students acquiring new competences for them to be successful in society. These are called 21st‐century competences that come as high‐skill competences – higher‐order thinking capacities and teamwork competences – and information and communication technologies (ICT) competences – technological, pedagogical and ethical. This study aims to determine the link between ICT competences and high‐skill competences. A correlational study was conducted whose sample was formed by 983 students studying degrees at the Universidad de Valencia (Spain), selected by non‐probabilistic incidental sampling and collecting information with two questionnaires. The results indicate a positive and statistically significant relation between ICT competences with the other two considered sets: higher‐order thinking capacities and teamwork competences. Moreover, pedagogical competences are more related with the two high‐skill competence sets. This suggests the need for training plans that favour learning 21st‐century competences and for stressing pedagogical competences in ICT. Lay Description: What is already known about this topic: University students require new competences to face a changing society.21st‐century competences are made up of ICT competences, higher‐order thinking capacities and teamwork competences.The empirical relation between ICT competences with higher‐order thinking capacities and teamwork competences has been little addressed.Few empirical studies have determined the contribution of each of the competence dimensions in that relation. What this paper adds: There is a positive relation between ICT competences and higher‐order thinking capacities and teamwork competences.Pedagogical competences –ICT competences‐ are more closely related to the two sets of high‐skill competences.Problem solving and the two teamwork competences contribute more to the relation with ICT competences. Implications for practice and/or policy: University system have to development training plans in the 21st century competences for the university student.University system have to promote specific training in pedagogical competences ‐ICT competences‐ for university student. [ABSTRACT FROM AUTHOR]

To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two‐factor structure of "Ethical and Privacy Expectations" and "Service Feature Expectations." As it stands, however, the SELAQ has only been validated with students from UK university, which is problematic on account of the interest in Learning Analytics extending beyond this context. Thus, the aim of the current work was to assess whether the translated SELAQ can be validated in three contexts (an Estonian, a Spanish, and a Dutch University). The findings show that the model provided acceptable fits in both the Spanish and Dutch samples, but was not supported in the Estonian student sample. In addition, an assessment of local fit is undertaken for each sample, which provides important points that need to be considered in future work. Finally, a general comparison of expectations across contexts is undertaken, which are discussed in relation to the General Data Protection Regulation (2018). Lay Description: What is currently known about the subject matter: Accounting for student expectations allows for a service that is meaningful.SELAQ measures student expectations towards Learning Analytics services.The 12 items of the SELAQ can be explained by a two‐factor structure (Ethical and Privacy Expectations and Service Feature Expectations). What their paper adds to this: Validation of the SELAQ in three contextsA discussion of localized sources of strainAn assessment of measurement quality in each contextA general comparison of student expectations across contexts The implications of study findings for practitioners: SELAQ can be used with Spanish and Dutch students.SELAQ responses provide a much needed input from end‐users in Learning Analytics implementations. [ABSTRACT FROM AUTHOR]

This paper studies how the integration of group awareness tools in the knowledge management system called KnowCat (Knowledge Catalyser), which promotes collaborative knowledge construction, may both foster the students' perception about the meaningfulness of visualization of group awareness information and promote better collaborative processes as well as enhance better task performance. Forty-seven university students participated in a research study, where one group of 23 students used KnowCat without the awareness console (non-awareness group); the other 24 students used KnowCat with the awareness console (awareness group). Both groups used KnowCat during one semester. Data analysis revealed that the awareness group means were higher than those of the non-awareness group in terms of participation, cognitive and metacognitive learning activities, and task performance. Moreover, students revealed that knowing what, where and how much their classmates were contributing acted as positive feedback by encouraging participation and orienting their own behaviour and their contribution to the collaborative work. In this paper, we claim that the visualization group awareness information in KnowCat, a utility allowing students to visualize and track what, where, how much and how often other participants contributed to the KnowCat knowledge area, had a positive impact on the students' collaborative behaviour. [ABSTRACT FROM AUTHOR]

When students solve problems on the Internet, they have to find a balance between quickly scanning large sections of information in web pages and deeply processing those that are relevant for the task. We studied how high school students articulate scanning and deeper processing of information while answering questions using a Wikipedia document, and how their reading comprehension skills and the question type interact with these processes. By analyzing retrospective think-aloud protocols and eye-tracking measures, we found that scanning of information led to poor hypertext comprehension, while deep processing of information produced better performance, especially in location questions. This relationship between scanning, deep processing, and performance was qualified by reading comprehension skills in an unexpected way: Scanning led to lower performance especially for good comprehenders, while the positive effect of deep processing was independent of reading comprehension skills. We discussed the results in light of our current knowledge of Internet problem solving. [ABSTRACT FROM AUTHOR]