Max Louwerse
@tilburguniversity.edu
Tilburg University
RESEARCH, TEACHING, or OTHER INTERESTS
General Psychology, Artificial Intelligence, Language and Linguistics
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Evy van Weelden, Travis J. Wiltshire, Maryam Alimardani, and Max M. Louwerse
Elsevier BV
H. A. T. van Limpt-Broers, M. Postma, E. van Weelden, S. Pratesi, and M. M. Louwerse
Springer Science and Business Media LLC
AbstractThe Overview Effect is a complex experience reported by astronauts after viewing Earth from space. Numerous accounts suggest that it leads to increased interconnectedness to other human beings and environmental awareness, comparable to self-transcendence. It can cause fundamental changes in mental models of the world, improved well-being, and stronger appreciation of, and responsibility for Earth. From a cognitive perspective, it is closely linked to the emotion of awe, possibly triggered by the overwhelming perceived vastness of the universe. Given that most research in the domain focuses on self-reports, little is known about potential neurophysiological markers of the Overview Effect. In the experiment reported here, participants viewed an immersive Virtual Reality simulation of a space journey while their brain activity was recorded using electroencephalography (EEG). Post-experimental self-reports confirmed they were able to experience the Overview Effect in the simulated environment. EEG recordings revealed lower spectral power in beta and gamma frequency bands during the defining moments of the Overview Effect. The decrease in spectral power can be associated with reduced mental processing, and a disruption of known mental structures in this context, thereby providing more evidence for the cognitive effects of the experience.
Guido M. Linders and Max M. Louwerse
Springer Science and Business Media LLC
AbstractMost natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly none for those researchers who lack deep computational linguistic knowledge or programming skills. Yet, for interdisciplinary researchers in a variety of fields, ranging from psycholinguistics, social psychology, cognitive psychology, education, to literary studies, there certainly is a need for such a cross-linguistic tool. In the current paper, we present Lingualyzer (https://lingualyzer.com), an easily accessible tool that analyzes text at three different text levels (sentence, paragraph, document), which includes 351 multidimensional linguistic measures that are available in 41 different languages. This paper gives an overview of Lingualyzer, categorizes its hundreds of measures, demonstrates how it distinguishes itself from other text quantification tools, explains how it can be used, and provides validations. Lingualyzer is freely accessible for scientific purposes using an intuitive and easy-to-use interface.
Guido M. Linders and Max M. Louwerse
Springer Science and Business Media LLC
Laduona Dai, Veronika Kritskaia, Evelien van der Velden, Reinder Vervoort, Marlieke Blankendaal, Merel M. Jung, Marie Šafář Postma, and Max M. Louwerse
Wiley
AbstractBackgroundThe integration of Text‐to‐Speech (TTS) and virtual reality (VR) technologies in K‐12 education is an emerging trend. However, little is known about how students perceive these technologies and whether these technologies effectively facilitate learning.ObjectivesThis study aims to investigate the perception and effectiveness of TTS voices and VR agents in a K‐12 classroom setting, with a focus on information recall.MethodsUsing a recent TTS architecture, we developed four different synthetic voices based on 5, 10, 15 and 20 h of training materials. Two experiments were conducted involving students in a K‐12 setting. The first experiment examined students' evaluations of TTS voices with varying hours of training material and the impact on information recall. The second experiment assessed the effect of pairing TTS voices with a VR agent on students' perception and recall performance.Results and ConclusionsHuman voices received superior quality ratings over TTS voices within the classroom context. The integration of a VR agent was found to enhance the perception of TTS voices, aligning with existing literature on the positive impact of virtual agents on speech synthesis. However, this incorporation did not translate to improved recall, suggesting that the student focus may have been compromised by the VR agent's novelty and its design limitations.
Evy van Weelden, Carl W. E van Beek, Maryam Alimardani, Travis J. Wiltshire, Wietse D. Ledegang, Eric L. Groen, and Max M. Louwerse
IEEE
Quantifying workload is necessary for effective and personalized flight training of student pilots: their workload must not be too low (risk of boredom) nor too high (overload). Passive brain-computer interfaces (pBCIs) allow for measurement of an individual’s workload from their brain activity, however, the performance of pBCIs remains suboptimal due to individual differences and lack of data for classifier training. In this study, we addressed this problem by combining EEG and behavioral data from six novice military pilots who performed a flight task in Virtual Reality in order to develop calibration-free pBCIs for workload assessment. Three pBCI classifiers were trained on EEG spectral power features from theta (4-8 Hz), alpha (8-13 Hz) and beta (13-30 Hz) bands, and an additional behavioral feature derived from pilots’ control inputs on the (joy)stick. The models reached average classification accuracies of 0.82, 0.78, and 0.78. The key feature driving the models’ performance was EEG theta power from several regions of the brain. The pilots’ control inputs (i.e., behavioral feature) did not contribute to the model performance, however, it moderately correlated with several EEG theta power features. The results demonstrate the feasibility of a subject-independent pBCI for calibration-free classification of workload in pilots as well as the importance of theta power at frontal and centro-parietal areas as a metric for real-time monitoring of workload. The use of behavioral control inputs together with fewer but highly predictive EEG features warrants further research.
H. Anna T. van Limpt-Broers, Marie Postma, and Max M. Louwerse
Springer Science and Business Media LLC
AbstractTransformative experiences in an individual’s life have a lasting impact on identity, belief system, and values. At the core of these experiences is the complex emotion of awe that promotes learning, making it worthwhile to study from an educational point of view. Drawing studies may provide a useful measure of awe in children—one that is more intuitive and attractive than questionnaires alone. Previous studies conducted with adults indicated that the diminished self, associated with transformative experiences, manifests in an actual decrease in size for figures representing the self in drawings. In the current study, self-representation was investigated in drawings of 10- to 12-year-old primary school children within the context of an immersive virtual reality (VR) experience that elicits the overview effect, known to lead to an intense apperception of awe. We did not replicate the adult findings regarding self-size in this younger age group. However, details and complexity in children’s drawings appeared to be impacted by the awe-elicitation procedure in VR. These elements subsequently correlated to learning gains instead of the overview effect, indicating that this measure could be linked to cognitive ability. The findings of the current study contribute to a better understanding of how drawings reflect self-transcendental experiences; however, they also reveal that in younger age groups, they are not necessarily reflected in decreased self-size.
Guido M. Linders and Max M. Louwerse
Wiley
AbstractWhat role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency‐based, machine learning, and deep learning methods all yield similar performance. Classification accuracies, moreover, generally do not explain which specific cues yield high performance. Using a cognitive science approach, in two analyses, we systematically investigated the role of cues in the surface structure of the utterance and cues of the surrounding context individually and combined. By comparing the explained variance, rather than the prediction accuracy of these cues in a logistic regression model, we found that (1) while surface and contextual linguistic cues can complement each other, surface linguistic cues form the backbone in human dialog act identification, (2) with word frequency statistics being particularly important for the dialog act, and (3) the similar trends across corpora, despite differences in the type of dialog, corpus setup, and dialog act tagset. The importance of surface linguistic cues in dialog act classification sheds light on how both computers and humans take advantage of these cues in speech act recognition.
Angelica M. Tinga, Nick S. Menger, Tycho T. de Back, and Max M. Louwerse
Hogrefe Publishing Group
Abstract: Research in young adults has demonstrated that neurophysiological measures are able to provide insight into learning processes. However, to date, it remains unclear whether neurophysiological changes during learning in older adults are comparable to those in younger adults. The current study addressed this issue by exploring age differences in changes over time in a range of neurophysiological outcome measures collected during visuomotor sequence learning. Specifically, measures of electroencephalography (EEG), skin conductance, heart rate, heart rate variability, respiration rate, and eye-related measures, in addition to behavioral performance measures, were collected in younger ( Mage = 27.24 years) and older adults ( Mage = 58.06 years) during learning. Behavioral responses became more accurate over time in both age groups during visuomotor sequence learning. Yet, older adults needed more time in each trial to enhance the precision of their movement. Changes in EEG during learning demonstrated a stronger increase in theta power in older compared to younger adults and a decrease in gamma power in older adults while increasing slightly in younger adults. No such differences between the two age groups were found on other neurophysiological outcome measures, suggesting changes in brain activity during learning to be more sensitive to age differences than changes in peripheral physiology. Additionally, differences in which neurophysiological outcomes were associated with behavioral performance on the learning task were found between younger and older adults. This indicates that the neurophysiological underpinnings of learning may differ between younger and older adults. Therefore, the current findings highlight the importance of taking age into account when aiming to gain insight into behavioral performance through neurophysiology during learning.
Julija Vaitonytė, Maryam Alimardani, and Max M. Louwerse
Elsevier BV
Guido M. Linders and Max M. Louwerse
Springer Science and Business Media LLC
AbstractThe ubiquitous inverse relationship between word frequency and word rank is commonly known as Zipf’s law. The theoretical underpinning of this law states that the inverse relationship yields decreased effort in both the speaker and hearer, the so-called principle of least effort. Most research has focused on showing an inverse relationship only for written monolog, only for frequencies and ranks of one linguistic unit, generally word unigrams, with strong correlations of the power law to the observed frequency distributions, with limited to no attention to psychological mechanisms such as the principle of least effort. The current paper extends the existing findings, by not focusing on written monolog but on a more fundamental form of communication, spoken dialog, by not only investigating word unigrams but also units quantified on syntactic, pragmatic, utterance, and nonverbal communicative levels by showing that the adequacy of Zipf’s formula seems ubiquitous, but the exponent of the power law curve is not, and by placing these findings in the context of Zipf’s principle of least effort through redefining effort in terms of cognitive resources available for communication. Our findings show that Zipf’s law also applies to a more natural form of communication—that of spoken dialog, that it applies to a range of linguistic units beyond word unigrams, that the general good fit of Zipf’s law needs to be revisited in light of the parameters of the formula, and that the principle of least effort is a useful theoretical framework for the findings of Zipf’s law.
S. M. Ali Mousavi, Wendy Powell, Max M. Louwerse, and Andrew T. Hendrickson
Frontiers Media SA
Introduction: There is a rising interest in using virtual reality (VR) applications in learning, yet different studies have reported different findings for their impact and effectiveness. The current paper addresses this heterogeneity in the results. Moreover, contrary to most studies, we use a VR application actually used in industry thereby addressing ecological validity of the findings.Methods and Results of Study1: In two studies, we explored the effects of an industrial VR safety training application on learning. In our first study, we examined both interactive VR and passive monitor viewing. Using univariate, comparative, and correlational analytical approaches, the study demonstrated a significant increase in self-efficacy and knowledge scores in interactive VR but showed no significant differences when compared to passive monitor viewing. Unlike passive monitor viewing, however, the VR condition showed a positive relation between learning gains and self-efficacy.Methods and Results of Study2: In our subsequent study, a Structural Equation Model (SEM) demonstrated that self-efficacy and users’ simulation performance predicted the learning gains in VR. We furthermore found that the VR hardware experience indirectly predicted learning gains through self-efficacy and user simulation performance factors.Conclusion/Discussion of both studies: Conclusively, the findings of these studies suggest the central role of self-efficacy to explain learning gains generalizes from academic VR tasks to those in use in industry training. In addition, these results point to VR behavioral markers that are indicative of learning.
Tycho T. De Back, Angelica M. Tinga, and Max M. Louwerse
Informa UK Limited
ABSTRACT
Immersive virtual environments hold unexplored potential to scaffold and stimulate learning in multiple ways for the purpose of increasing potential learning gains. Yet, the number of implementations in educational settings remains very limited. One reason for limited implementation of immersive virtual environment applications may be a lack of recommendations for their effective design. Building on an extensive theoretical framework, this paper provides such recommendations, specific to immersive educational settings. The recommendations are divided into strategies to optimize cognitive load, foster collaborative learning, leverage platform-specific affordances, mitigate platform-specific limitations and to obtain additional benefits. We illustrate the implementation of these recommendations using a novel collaborative virtual reality environment shown to yield learning gains in two prior studies. Moreover, we detail how a non-invasive and cost-effective feature of automated performance analysis can monitor learning gains in collaborative virtual reality environments. The recommendations based on the example of a collaborative virtual reality environment pave the way for more such implementations to maximize benefits for learners and educators alike.
Julija Vaitonytė, Maryam Alimardani, and Max M. Louwerse
Springer Science and Business Media LLC
AbstractVirtual faces have been found to be rated less human-like and remembered worse than photographic images of humans. What it is in virtual faces that yields reduced memory has so far remained unclear. The current study investigated face memory in the context of virtual agent faces and human faces, real and manipulated, considering two factors of predicted influence, i.e., corneal reflections and skin contrast. Corneal reflections referred to the bright points in each eye that occur when the ambient light reflects from the surface of the cornea. Skin contrast referred to the degree to which skin surface is rough versus smooth. We conducted two memory experiments, one with high-quality virtual agent faces (Experiment 1) and the other with the photographs of human faces that were manipulated (Experiment 2). Experiment 1 showed better memory for virtual faces with increased corneal reflections and skin contrast (rougher rather than smoother skin). Experiment 2 replicated these findings, showing that removing the corneal reflections and smoothening the skin reduced memory recognition of manipulated faces, with a stronger effect exerted by the eyes than the skin. This study highlights specific features of the eyes and skin that can help explain memory discrepancies between real and virtual faces and in turn elucidates the factors that play a role in the cognitive processing of faces.
Laduona Dai, Merel M. Jung, Marie Postma, and Max M. Louwerse
Elsevier BV
Laduona Dai, Veronika Kritskaia, Evelien van der Velden, Merel M. Jung, Marie Postma, and Max M. Louwerse
ACM
With increased interest in the use of virtual avatars for educational purposes, there is a growing need for high-quality text-to-speech solutions. However, the effects of using synthesized speech in educational applications for younger listeners are still unclear as past findings have been inconsistent and most of them have been obtained in a lab setting with adult assessors. Next to that, it is unclear how much training material is needed for high quality speech synthesis. Particularly for low resource languages, the assumption that good quality synthesized speech requires substantial amounts of vocal recordings to train may be hindering the development of TTS-based solutions. In this study, we created four Dutch text-to-speech (TTS) models from different amounts of training material and evaluated the models in terms of voice perception and recall with K12 students in a classroom environment. Results showed that while the original human voice outperformed the synthesized voices in terms of the listening experience and knowledge test score, more hours of training material did not necessarily result in better outcomes suggesting that 10-15 hours of speech material might be sufficient for training a Dutch TTS. A weak positive correlation was found between listening experience and knowledge test performance, with the low listening effort being the most important factor. This outcome suggests that comprehensibility is likely the most important TTS feature for educational applications.
Evy van Weelden, Maryam Alimardani, Travis J. Wiltshire, and Max M. Louwerse
Elsevier BV
Guido M. Linders, Julija Vaitonytė, Maryam Alimardani, Kiril O. Mitev, and Max M. Louwerse
ACM
We introduce an interactive embodied conversational agent for deployment in the healthcare sector. The agent is operated by a software architecture that integrates speech recognition, dialog management, and speech synthesis, and is embodied by a virtual human face developed using photogrammetry techniques. These features together allow for real-time, face-to-face interactions with human users. Although the developed software architecture is domain-independent and highly customizable, the virtual agent will initially be applied to healtcare domain. Here we give an overview of the different components of the architecture.
Evy van Weelden*, Travis J. Wiltshire, Maryam Alimardani, and Max M. Louwerse
SAGE Publications
Virtual reality (VR) offers a training environment that promotes increased learning and performance. However, to what extent VR flight simulations offer increased performance compared to less-immersive simulators is not clear, and neither are their underlying cognitive aspects. In a within-subject experiment, we compared fight performance and subjective measures of workload, presence, and engagement in two flight training environments (Desktop and VR) on two flight tasks of equal difficulty (changing speed and performing turns). No differences were observed in the flight performance between these conditions. However, participants reported higher presence and engagement in the VR training environment. Additionally, we found a correlation between subjective workload and flight performance in the Desktop condition, but not in VR. We conclude that VR is promising for basic flight training tasks and encourage future work to explore this further by investigating neurophysiological indices of workload and engagement and establishing relationships between presence, workload, and flight performance.
Gianluca Guglielmo, Travis Wiltshire, and Max Louwerse
SCITEPRESS - Science and Technology Publications
Physiological data have shown to be useful in tracking and differentiating cognitive processes in a variety of experimental tasks, such as numerical skills and arithmetic tasks. Numerical skills are critical because they are strong predictors of levels of ability in cognitive domains such as literacy, attention, and understanding contexts of risk and uncertainty. In this work, we examined frontal and parietal electroencephalogram signals recorded from 36 healthy participants performing a mental arithmetic task. From each signal, six RQA-based features (Recurrence Rate, Determinism, Laminarity, Entropy, Maximum Diagonal Line Length and, Average Diagonal Line Length) were extracted and used for classification purposes to discriminate between participants performing proficiently and participants performing poorly. The results showed that the three classifiers implemented provided an accuracy above 0.85 on 5-fold cross-validation, suggesting that such features are effective in detecting performance independently from the specific classifiers used. Compared to other successful methods, RQA-based features have the potential to provide insights into the nature of the physiological dynamics and the patterns that differentiate levels of proficiency in cognitive tasks.
Tycho T. de Back, Angelica M. Tinga, and Max M. Louwerse
Springer Science and Business Media LLC
AbstractImmersive virtual reality is increasingly regarded as a viable means to support learning. Cave Automatic Virtual Environments (CAVEs) support immersive learning in groups of learners, and is of potential interest for educational institutions searching for novel ways to bolster learning in their students. In previous work we have shown that the use of a CAVE-based virtual learning environment yielded higher learning gains compared to conventional textbook study. Yet, few prior studies have explored the circumstances that yield a trade-off between learning gains and the practical feasibility of providing immersive learning to large student numbers. To gain insight into these circumstances the current study examined two factors: (1) group size (small, medium and large), and (2) time of application (pre-, mid- and late-term of a course). Results indicated learning gains were present for all group sizes and application time periods, with highest learning gains in smaller groups. Learning gains were consistent across application time periods. Additionally, structural equation modeling was applied to assess how learning may result from the use of immersive virtual reality. Results indicated technological virtual reality features predicted learning outcomes via self-reported usability but less so via self-reported presence. Based on the findings, recommendations are presented for effective immersive learning for different group size and application time period configurations. Taken together, the current study elucidates factors affecting learning in immersive virtual reality and facilitates its use in educational practice.
Evy van Weelden, Maryam Alimardani, Travis J. Wiltshire, and Max M. Louwerse
IEEE
Virtual reality (VR) has been used for training purposes in a wide range of industries, including education, healthcare, and defense. VR allows users to train in a safe and controlled digital environment while being immersed and highly engaged in a realistic task. One of its advantages is that VR can be combined with multiple wearable sensing technologies, allowing researchers to study (neuro)physiological and cognitive processes elicited by dynamic environments and adapt these simulations based on such processes. However, the potential of VR combined with neurotechnology to facilitate effective and efficient aviation training has not yet been fully explored. For instance, despite the growing interest in including VR as part of the training programs for military and commercial airlines pilots, it is still unclear what the effectiveness of VR is in short- and long-term training of pilots. This paper provides an overview of the state-of-the-art research in VR applications for aviation training and identifies challenges and future opportunities. We particularly discuss the potential of neurotechnology in objective measurement of training progress and providing real-time feedback during VR flight tasks. Overall, VR combined with neurotechnology for flight training holds promise to optimize individual learning progress.
Max Louwerse, Marie Postma, Maarten Horden, and Anton Sluijtman
Springer International Publishing
AbstractThe COVID-19 pandemic has disrupted the status quo in many areas of society, including education. At all educational levels, on-site lecturing had to switch instantaneously to an online mode of instruction. This transition was so straightforward, that the argument could be made for online education to become a permanent fixture, particularly if it is more efficient, cheaper, and more effective than traditional education. Extensive meta-analyses, however, show that most online teaching practices do not lead to better educational outcomes than the on-site alternatives. Worse yet, the traditional face-to-face mode of lecturing is ineffective in the absence of personalized interactions. The proposed solutions are offered by artificial intelligence research, including virtual reality, intelligent tutoring systems, and serious games—solutions that have so far not been extensively implemented in practice. The current health crisis provides our educational professionals with an opportunity to rethink their teaching practices and focus on applying these promising new alternatives.