Learning Analytics Framework for Improving Performance to Students through Educational Virtual Worlds

The development of an educational 3D virtual world requires a complex skillset, which includes programming, modeling, texturing, animating, and quest/level designing. When these skills are distributed across multiple workers, the workers must negotiate a shared understanding of their intermediate work products, which ultimately culminate in the virtual world. This paper is an ethnography of the intermediate work products (“artifacts”) and processes used in the development of Virtual Energy World—a 3D virtual world for instruction on sustainable energy issues. The resulting artifacts and processes have utility as a general development framework for both educational virtual worlds and video games.

The purpose of the article is to analyse the needs of general education schoolteachers’ data literacy skills that are important for the effective use of learning analytics in the teaching-learning process. The theoretical part of the article presents the idea of big data in education, highlights the aspects of pedagogical value of learning analytics technologies, provides the overview of learning analytic tools. Some overview and comparison of spread of learning analytics tools in general education schools in Lithuania and Germany is presented in the context of data-driven education. The empirical part of the article presents some results from a big qualitative study of teachers’ experiences applying learning analytics tools in teaching - learning process. The main question of the current research is what data literacy skills teachers need in order to use learning analytics tools and make data based pedagogical decisions. Semi-structured interviews were conducted with 10 Lithuanian and 9 German teachers from general education schools, who already have had experience in working with learning experience platforms (digital learning platforms that integrate learning analytics tools). Interview data were analysed by means of content analysis. The results of the qualitative study showed that in order to use learning analytics tools it is important for teachers to have such skills as: digital literacy, data collection, data analysis and interpretation, etc. Comparative analysis of informants’ answers showed that teachers in Lithuania and Germany expressed similar needs for data literacy skills.

Whilst students may find Educational Virtual World (EVWs) more visually appealing and enjoyable than reading the theory in a textbook, using an EVW does not guarantee learning. The exploratory and experiential nature that potentially can enhance learning, can also lack structure or apparent purpose and may not achieve the intended learning outcomes. This paper reports a study that sought to understand whether navigational tips based on patterns in navigation paths to predict student performance, measured by recall for events and material encountered in the EVW, would be useful to provide timely hints or encouragement to improve performance and/or make learning more efficient.

AI-driven learning analytics applications and tools in computer-supported collaborative learning: A systematic review

With the increase in online classes and our access to large amounts of learning and educational data, Learning Analytics (LA) has received much attention. LA is essential for student-centered education and can make a significant contribution to transforming the educational model. This paper describes the procedures and significance of LA and introduces classes on mechanical engineering using LA tools. In our class, we used the LEAF system consisting of BookRoll and LAView as the LA tool. By using the BookRoll to deliver explanations of pre-class assignments for a flipped classroom, we could analyze the learning activities in the LAView and monitor student understanding. Furthermore, we found a statistically significant difference in the time spent reading the material between the highest- and lowest-performing students.

El propósito del presente trabajo es desarrollar una propuesta didáctica para la enseñanza del ritmo basada en la implementación de una banda rítmica dirigida a los niños del quinto año de educación básica de la Unidad Educativa Delta, de la ciudad de Guayaquil, Ecuador. Y el objetivo principal es desarrollar una propuesta didáctica para los niños de quinto año de educación general básica que facilite el aprendizaje del ritmo a través de la formación de bandas rítmicas. Se ha considerado que es significativa, ya que si bien es cierto que en la educación musical se trabaja la rítmica, también lo es que la banda rítmica permitirá desarrollar en los niños la concentración, la memoria, la métrica y el pulso. Al desarrollar la propuesta didáctica para los niños, se facilitará el aprendizaje del ritmo a través de la formación de bandas rítmicas. Dentro del presente trabajo se usa el ritmo a través de los instrumentos. Para la ejecución de los ritmos se utilizan los siguientes instrumentos ordenados de una progresión menor a mayor dificultad.

Electricity load-shedding in South Africa has become a new challenge for students pursuing online learning following the Covid-19 outbreak. This article thus investigated the way load-shedding affects students in pursuing the Advanced Certificate in Teaching (ACT) programmes. Pre-Covid-19 and during load-shedding data between 2018 and 2022 was gathered and analysed using a descriptive learning analytics tool. The research took place at a South African university where the researcher is currently employed. Learning analytics data has been available for years, but it is now being effectively harnessed to improve learning and teaching through relatively recent developments in learning analytics tools. However, the load-shedding conundrum works against this objective of harnessing learning and teaching. Research has also shown that in the least developed countries, effective e-learning practices face significant barriers, primarily stemming from insufficient infrastructure, economic challenges, low levels of computer literacy, and the added challenge of power outages. Using a constructivist paradigm, the study employed a mixed qualitative approach, which included desktop historical data and semi-structured interviews. Three participants were purposely selected because of their role in overseeing ACT students situated in both rural and urban areas. The study revealed that numerous programmes were discontinued, enrollment declined, ACT Blended shifted to e-learning, persisting load-shedding conundrum affected e-learning, a low throughput rate, and digital illiteracy contributed to an increased rate of student dropouts. This research recommends that universities should embrace the evolution of e-learning through the digitalisation of learning processes to enhance efficiency. Keywords: Load-shedding, E-learning, Learning Analytics Tools, Declined Enrolment, Low Throughput Rate vs High Distinction Module Pass Rate

This paper examines youth storytelling during co-design of an identity-expressive educational game for learning data science.Using interaction analysis of co-design interviews with middle school students, we explore how storytelling allows participants to (a) use existing game elements to position themselves and (b) express their interests and identities through imagined game futures.We argue that analyzing youth's interactive storytelling and identity enactments during co-design can inform the development of game narratives that represent diverse youth.Our findings contribute to the design of inclusive virtual worlds for STEM learning that celebrate youth identities and experiences.We discuss implications for engaging youth voices in the co-design process and creating educational games that resonate with diverse learners. PurposeVideo games are important contexts for inclusive STEM learning, allowing players to explore and enact identities (Gaydos & Devane, 2019; Gee, 2014).However, designing educational games that connect to diverse players' lives and identities is a significant challenge.Our project employs youth co-design to create "The Isles of Ilkmaar," a virtual world that supports identity-expressive data science learning among diverse youth, particularly genderexpansive youth, cis-girls, and youth of color.In this paper, we explore storytelling as a method for engaging diverse youth in co-design.An initial analysis showed how storytelling within co-design activates youth expertise and imaginations, facilitating a transition from game players to game designers (Radke, et al., 2023).We now look more closely at storytelling episodes to understand youth's shifting positionalities within the co-design context, illustrating how storytelling allows youth to (a) refer to and take up existing game elements as resources for positioning themselves as designers and (b) author and animate imagined new game futures in which they can projectively identify (Gee, 2014) with the player character.By analyzing youth narratives through the lens of positioning, we aim to understand how youth contributions to co-design arise from and reflect the dual positionalities of game designer and future player, contributing to the understanding of how to design educational games that connect to diverse players' lives and identities.

Several studies have shown that complex nonlinear learning analytics (LA) techniques outperform the traditional ones. However, the actual integration of these techniques in automatic LA systems remains rare because they are generally presumed to be opaque. At the same time, the current reviews on LA in higher education point out that LA should be more grounded to the learning science with actual linkage to teachers and pedagogical planning. In this study, we aim to address these two challenges. First, we discuss different techniques that open up the decision-making process of complex techniques and how they can be integrated in LA tools. More precisely, we present various global and local explainable techniques with an example of an automatic LA process that provides information about different resources that can support student agency in higher education institutes. Second, we exemplify these techniques and the LA process through recently collected student agency data in four courses of the same content taught by four different teachers. Altogether, we demonstrate how this process—which we call explainable student agency analytics—can contribute to teachers’ pedagogical planning through the LA cycle.

Regardless of all the frameworks and models that have been proposed for starting Learning Analytics (LA) initiatives, LA adoption remains immature. LA research is still a growing field in some regions, and researchers and practitioners continue to experience institutional challenges for scaling LA adoption. Considering the need for using LA to improve student learning and program quality, it is important to bring stakeholders together to exchange ideas about how LA tools could be used in everyday practices. To meet this objective, this chapter presents the LALA Canvas: a conceptual model to support a participatory approach to LA adoption in higher education (HE). The LALA Canvas was developed within the LALA Project, and it proposes a template to guide group discussions at universities where LA adoption is still at an early stage. The LALA Canvas model has been used by the four Latin American universities affiliated with the LALA project and socialized with 371 HE stakeholders from universities from different Latin American countries, including Chile, Brazil, Costa Rica, and Perú. This chapter describes the LALA Canvas and the lessons learned from having used it to start conversations about the potential benefits of LA in different university settings.

Transparency and trustworthiness are among the key requirements for the ethical use of learning analytics (LA) and artificial intelligence (AI) in the context of social inclusion and equity. However, research on these issues pertaining to users is lacking, leaving it unclear as to how transparent and trustworthy current LA tools are for their users and how perceptions of these variables relate to user behaviour. In this study, we investigate user experiences of an LA tool in the context of career guidance, which plays a crucial role in supporting nonlinear career pathways for individuals. We review the ethical challenges of big data, AI, and LA in connection to career guidance and analyze the user experiences (N = 106) of the LA career guidance tool, which recommends study programs and institutions to users. Results indicate that the LA career guidance tool was evaluated as trustworthy but not transparent. Accuracy was found to be a stronger predictor for the intention to follow on the recommendations of the LA guidance tool than was understanding the origins of the recommendation. The user’s age emerged as an important factor in their assessment of transparency. We discuss the implications of these findings and suggest emphasizing accuracy in the development of LA tools for career guidance.

During the last few years, learning analytics (LA) has gained the interest of researchers in the field of education. Generally, LA is related with the development of methods that use educational data sets to support the learning process. Therefore, there is a need understanding how learners, educators, and institutions can best support this process. Thus, a framework is presented that tries to extend the collaborative three-dimensional virtual environments for educational by integrating a LA tool. The aim is to help the teacher to monitor and evaluate the students' learning process in these types of environments. It is the intention include a (1) comprehensive analysis of the currently available LA tools for educational, (2) design of a user-centered framework based the requirements gathered from the analysis, and (3) thorough evaluation of framework to allow identify possible behavior patterns of students within the environment, related to your preferences for materials and expertise.

Teacher regulation of cognitive activities during student collaboration: Effects of learning analytics

Despite promising outcomes in higher education, the widespread adoption of learning analytics remains elusive in various educational settings, with primary and secondary schools displaying considerable reluctance to embrace these tools. This hesitancy poses a significant obstacle, particularly given the prevalence of educational technology and the abundance of data generated in these environments. In contrast to higher education institutions that readily integrate learning analytics tools into their educational governance, high schools often harbor skepticism regarding the tools’ impact and returns. To overcome these challenges, this work aims to harness learning analytics to address critical areas, such as school dropout rates, the need to foster student collaboration, improving argumentation and writing skills, and the need to enhance computational thinking across all age groups. The goal is to empower teachers and decision makers with learning analytics tools that will equip them to identify learners in vulnerable or exceptional situations, enabling educational authorities to take suitable actions that are aligned with students’ needs; this could potentially involve adapting learning processes and organizational structures to meet the needs of students. This work also seeks to evaluate the impact of such analytics tools on education within a multi-dimensional and scalable domain, ranging from individual learners to teachers and principals, and extending to broader governing bodies. The primary objective is articulated through the development of a user-friendly AI-based dashboard for learning. This prototype aims to provide robust support for teachers and principals who are dedicated to enhancing the education they provide within the intricate and multifaceted social domain of the school.

The rapid advancement of digital technologies has transformed the landscape of education, with the metaverse emerging as a new and immersive learning platform.At the same time, gamification has proven to be a powerful pedagogical strategy for enhancing student engagement and motivation.The convergence of these two fields -educational virtual worlds and game-based learning -opens new avenues for experiential and interactive education.This study explores the integration of gamification into educational virtual environments in the metaverse, focusing on how game design elements, such as points, badges, levels, and collaborative missions, can be incorporated to support pedagogical goals.Building on the existing literature, this research proposes a methodology for designing immersive, game-enriched educational experiences.The study examines both the benefits and limitations of such applications, highlighting the potential of collaborative design as a means to enhance creativity, motivation, and deeper engagement.