Roberto Martinez-Maldonado

Monash University (Australia) · Faculty of Information Technology

Multimodal Learning Analytics (MMLA) leverages advanced sensing technologies and artificial intelligence to capture complex learning processes, but integrating diverse data sources into cohesive insights remains challenging. This study introduces a novel methodology for integrating latent class analysis (LCA) within MMLA to map monomodal behavioura...

Learning analytics dashboards (LADs) simplify complex learner data into accessible visualisations, providing actionable insights for educators and students. However, their educational effectiveness has not always matched the sophistication of the technology behind them. Explanatory and interactive LADs, enhanced by generative AI (GenAI) chatbots, h...

The rapid integration of generative artificial intelligence (GenAI) technology into education requires precise measurement of GenAI literacy to ensure that learners and educators possess the skills to engage with and critically evaluate this transformative technology effectively. Existing instruments often rely on self-reports, which may be biased....

Despite growing interest in applying human-centred design methods to create learning analytics (LA) systems, most efforts have concentrated on initial design phases, with limited exploration of how LA tools and practices can co-evolve during the actual learning and teaching activities. This paper examines how a human-centred LA dashboard can be fur...

The proliferation of educational technologies has generated unprecedented volumes of diverse, multimodal learner data, offering rich insights into learning processes and outcomes. However, leveraging this complex, multimodal data requires advanced analytical methods. While Multimodal Learning Analytics (MMLA) offers promise for exploring this data,...

Embodied collaborative learning, intertwining verbal and physical behaviors, is an intricate learning process demanding a multifaceted approach for comprehensive understanding. Prior studies in this field have often neglected the temporal dynamics and the interplay between verbal and bodily behaviors in collaborative learning settings. This study b...

In highly immersive, team-based healthcare simulations, students must collaborate effectively to complete open-ended learning tasks. These often require students to move among multiple locations within the physical learning space, 1 requiring the development of effective communication tactics to manage complex team dynamics and multiple concurrent...

Physiological synchrony and arousal are increasingly utilised to understand students' affective and cognitive states, such as stress, which can influence their learning performance and satisfaction in collaborative settings. However, it remains uncertain whether these physiological indicators can meaningfully reflect students' stress and learning p...

Feedback is essential in learning. The emerging concept of feedback literacy underscores the skills students require for effective use of feedback. This highlights students’ responsibilities in the feedback process. Yet, there is currently a lack of mechanisms to understand how students make sense of feedback and whether they act on it. This gap ma...

Background Feedback is central to formative assessments but aligns with a one‐way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active...

Multimodal learning analytics (MMLA) offers the potential to provide evidence‐based insights into complex learning phenomena such as collaborative learning. Yet, few MMLA applications have closed the learning analytics loop by being evaluated in real‐world educational settings. This study evaluates the effectiveness of an MMLA solution in enhancing...

Effective collaboration and teamwork skills are critical in high‐risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real‐world scenarios, enabling students to safely improve their teamwork abilities. In such learni...

Integrating generative AI (GAI) into higher education is crucial for preparing a future generation of GAI-literate students. Yet a thorough understanding of the global institutional adoption policy remains absent, with most of the prior studies focused on the Global North and the promises and challenges of GAI, lacking a theoretical lens. This stud...

This special issue aims to bring together contributions that have used MMLA methods in the wild. Contributions will discuss obstacles to the use of multimodal data in real-world settings, share lessons learned from current projects, and propose productive next steps for the field to become more ecologically relevant.

Learning analytics dashboards (LADs) serve as pivotal tools in transforming complex learner data into actionable insights for educational stakeholders. Despite their potential, the effectiveness of LADs, particularly the visualisations they utilise, has been under scrutiny. Concerns have been raised about their potential to cause cognitive overload...

There is a growing interest in creating Learning Analytics (LA) systems that incorporate student perspectives. Yet, many LA systems still lean towards a technology-centric approach, potentially overlooking human values and the necessity of human oversight in automation. Although some recent LA studies have adopted a human-centred design stance, the...

Advancements in Multimodal Learning Analytics (MMLA) have the potential to enhance the development of effective teamwork skills and foster reflection on collaboration dynamics in physical learning environments. Yet, only a few MMLA studies have closed the learning analytics loop by making MMLA solutions immediately accessible to educators to suppor...

Dashboards are increasingly used in education to provide teachers and students with insights into learning. Yet, existing dashboards are often criticised for their failure to provide the contextual information or explanations necessary to help students interpret these data. Data Storytelling (DS) is emerging as an alternative way to communicate ins...

Even though the engagement in self-regulated learning (SRL) has been shown to boost academic performance, SRL skills of many learners remain underdeveloped. They often struggle to productively navigate multiple cognitive, affective, metacognitive and motivational (CAMM) processes in SRL. To provide learners with the required SRL support, it is esse...

Learning analytics (LA) dashboards are becoming increasingly available in various learning settings. However, teachers may face challenges in understanding and interpreting the data visualisations presented on those dashboards. In response to this, some LA researchers are incorporating visual cueing techniques, like data storytelling (DS), into LA...

Human‐Centred Learning Analytics (HCLA) has emerged in the last 5 years as an active sub‐topic within Learning Analytics, drawing primarily on the theories and methods of Human‐Computer Interaction (HCI). HCLA researchers and practitioners are adopting and adapting HCI theories/methods to meet the challenge of meaningfully engaging educational stak...

Effective collaboration and team communication are critical across many sectors. However, the complex dynamics of collaboration in physical learning spaces, with overlapping dialogue segments and varying participant interactions, pose assessment challenges for educators and self-reflection difficulties for students. Epistemic network analysis (ENA)...

Generative artificial intelligence (GenAI), exemplified by ChatGPT, Midjourney, and other state-of-the-art large language models and diffusion models, holds significant potential for transforming education and enhancing human productivity. While the prevalence of GenAI in education has motivated numerous research initiatives, integrating these tech...

Wearable positioning sensors are enabling unprecedented opportunities to model students’ procedural and social behaviours during collaborative learning tasks in physical learning spaces. Emerging work in this area has mainly focused on modelling group-level interactions from low-level x-y positioning data. Yet, little work has utilised such data to...

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing and artificial intelligence algorithms to collect rich data about learning activities that unfold in physical spaces. The analysis of these data is opening exciting new avenues for both studying and supporting learning. Yet, practical and logistical challenges com...

Socio-spatial learning analytics (SSLA) is an emerging area within learning analytics research that seeks to un-cover valuable educational insights from individuals’ social and spatial data traces. These traces are capturedautomatically through sensing technologies in physical learning spaces, and the research is commonly based onthe theoretical fo...

There has been a proliferation of learning analytics (LA) interfaces designed to support teachers, such as LA dashboards. However, although teacher dashboards have been extensively studied, there is limited understanding of the relationship between single-page or multi-page dashboard designs and the cognitive demands placed on teachers to use them....

The notion of Human-Centred Learning Analytics (HCLA) is gaining traction as educators and learning analytics (LA) researchers recognise the need to align analytics and artificial intelligence (AI) technologies with specific educational contexts. This has led an increasing number of researchers to adopt approaches, such as co-design and participato...

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are concerns...

In embodied team learning activities, students are expected to learn to collaborate with others while freely moving in a physical learning space to complete a shared goal. Students can thus interact in various team configurations, resulting in increased complexity in their communication dynamics since unrelated dialogue segments can concurrently ha...

Advancements in sensing technologies, artificial intelligence (AI) and multimodal learning analytics (MMLA) are making it possible to model learners’ affective and physiological states. Physiological synchrony and arousal have been increasingly used to unpack students’ affective and cognitive states (e.g., stress), which can ultimately affect their...

Sensing technologies are rapidly dropping in price and improving the quality of data acquisition. It is therefore expected that sensing technologies, paired with artificial intelligence algorithms, will become a common part of the educational researcher’s toolkit to unobtrusively measure learning phenomena in years to come. In this section, we lear...

In embodied team learning activities, students are expected to learn to collaborate with others while freely moving in a physical learning space to complete a shared goal. Students can thus interact in various team configurations, resulting in increased complexity in their communication dynamics since unrelated dialogue segments can concurrently ha...

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (e.g., question generation, feedback provision, and essay grading), there are concer...

In recent years, there has been a growing interest in creating multimodal learning analytics (LA) systems that automatically analyse students’ states that are hard to see with the "naked eye", such as cognitive load and stress levels, but that can considerably shape their learning experience. A rich body of research has focused on detecting such as...

Capturing data on socio-spatial behaviours is essential in obtaining meaningful educational insights into collaborative learning and teamwork in co-located learning contexts. Existing solutions, however, have limitations regarding scalability and practicality since they rely largely on costly location tracking systems, are labour-intensive, or are...

Embodied team learning is a form of group learning that occurs in co-located settings where students need to interact with others while actively using resources in the physical learning space to achieve a common goal. In such situations, communication dynamics can be complex as team discourse segments can happen in parallel at different locations o...

Collocated teamwork remains a pervasive practice across all professional sectors. Even though live observations and video analysis have been utilized for understanding embodied interaction of team members, these approaches are impractical for scaling up the provision of feedback that can promote developing high-performance teamwork skills. Enrichin...

Feedback plays a crucial role in learning. Yet, higher education continues to face challenges regarding facilitating effective feedback processes. One of the challenges is the difficulty to track how students interact with feedback and the impact of feedback on learning outcomes. Learning analytics (LA) has opened up opportunities to enhance feedba...

Background Previous studies have demonstrated that students who are engaged in learning tasks and make errors before receiving instruction on how to complete them, achieve better learning outcomes than students who first receive instruction and then complete the learning activities with the aim of avoiding errors. Although simulation literature oft...

Research on learning spaces and their impact on teaching and learning has been a field of inquiry for decades. Yet, technological advances regarding data capture and analysis tools are opening both new opportunities and challenges in this area. This chapter illustrates the potential key role of multimodal learning analytics (MMLA) in advancing lear...

Background: Stringent public health measures have been shown to influence the transmission of SARS-CoV-2 within school environments. We investigated the potential transmission of SARS-CoV-2 in a primary school setting with and without public health measures, using fine-grained physical positioning traces captured before the COVID-19 pandemic. Met...

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them followi...

Simulation‐based learning provides students with unique opportunities to develop key procedural and teamwork skills in close‐to‐authentic physical learning and training environments. Yet, assessing students' performance in such situations can be challenging and mentally exhausting for teachers. Multimodal learning analytics can support the assessme...

Background Productive failure simulations require students to participate in a simulation before receiving instruction. This approach contrasts with traditional simulations that typically begin with instruction followed by the simulation. Although previous studies have demonstrated that productive failure facilitates meaningful learning outcomes, s...

There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explan...

One of the ultimate goals of several learning analytics (LA) initiatives is to close the loop and support students’ and teachers’ reflective practices. Although there has been a proliferation of end-user interfaces (often in the form of dashboards), various limitations have already been identified in the literature such as key stakeholders not bein...

Multimodal Learning Analytics (MMLA) innovations are commonly aimed at supporting learners in physical learning spaces through state-of-the-art sensing technologies and analysis techniques. Although a growing body of MMLA research has demonstrated the potential benefits of sensor-based technologies in education, whether their use can be scalable, s...

Teacher’s in-class positioning and interaction patterns (termed spatial pedagogy) are an essential part of their classroom management and orchestration strategies that can substantially impact students’ learning. Yet, effective management of teachers’ spatial pedagogy can become increasingly challenging as novel architectural designs, such as open...

Identifying students facing difficulties and providing them with timely support is one of the educator's key responsibilities. Yet, this task is becoming increasingly challenging as the complexity of physical learning spaces grows, along with the emergence of novel educational technologies and classroom designs. There has been substantial research...

Fast improvements in computing power and Artificial Intelligence (AI) algorithms enable us to automate important decisions that shape our everyday lives, and drive workplace transformations. It is predicted that many people will find themselves unprepared to deal with high degrees of change and uncertainty, increasingly posed by AI in some sectors....

The proliferation of AI in many aspects of human life—from personal leisure, to collaborative professional work, to global policy decisions—poses a sharp question about how to prepare people for an interconnected, fast-changing world which is increasingly becoming saturated with technological devices and agentic machines. What kinds of capabilities...

Rhythmic skills are fundamental in social partner dance. Yet, large class sizes and time constraints often make it challenging for teachers to assess learners’ rhythmic skills to provide constructive feedback. As motion sensors are becoming widely available and embedded in most smartphones, it is also becoming feasible to create models of anatomica...

Over the last ten years learning analytics (LA) has grown from a hypothetical future into a concrete field of inquiry and a global community of researchers and practitioners. Although the LA space may appear sprawling and complex, there are some clear through-lines that the new student or interested practitioner can use as entry points. Four of the...