Multimodal Technologies and Interaction

18 pages, 2597 KiB

Open AccessArticle

A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM

by Rima Shishakly, Mohammed Amin Almaiah, Shaha Al-Otaibi, Abdalwali Lutfi, Mahmaod Alrawad and Ahmed Almulhem

Multimodal Technol. Interact. 2023, 7(9), 92; https://doi.org/10.3390/mti7090092 - 20 Sep 2023

Viewed by 1698

Abstract

Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model [...] Read more.

Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model was developed, combining the TAM with additional new determinants, including perceived security, perceived trust, perceived risk, and service quality. The primary goal of this model is to assess the adoption of m-learning apps among users in university settings. To evaluate the proposed model, SEM was utilized to test the research model. The findings of the study highlight the critical roles of perceived security, perceived trust, and service quality in promoting the adoption of m-learning apps. Moreover, the results indicate that perceived risk negatively impacts both students’ trust and their attitudes towards using mobile learning services. The study reveals that the perceived trust, and service quality factors positively influence students’ attitudes towards adopting m-learning apps. These research findings hold significant implications for universities and academia, offering valuable insights to devise effective strategies for increasing the utilization of m- learning services among students. By gaining a deeper understanding of students’ perceptions and acceptance, universities can optimize their m-learning offerings to cater to students’ needs and preferences more effectively. Full article

(This article belongs to the Special Issue Designing EdTech and Virtual Learning Environments)

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22 pages, 724 KiB

Open AccessArticle

Semantic Interest Modeling and Content-Based Scientific Publication Recommendation Using Word Embeddings and Sentence Encoders

by Mouadh Guesmi, Mohamed Amine Chatti, Lamees Kadhim, Shoeb Joarder and Qurat Ul Ain

Multimodal Technol. Interact. 2023, 7(9), 91; https://doi.org/10.3390/mti7090091 - 15 Sep 2023

Viewed by 2112

Abstract

The fast growth of data in the academic field has contributed to making recommendation systems for scientific papers more popular. Content-based filtering (CBF), a pivotal technique in recommender systems (RS), holds particular significance in the realm of scientific publication recommendations. In a content-based [...] Read more.

The fast growth of data in the academic field has contributed to making recommendation systems for scientific papers more popular. Content-based filtering (CBF), a pivotal technique in recommender systems (RS), holds particular significance in the realm of scientific publication recommendations. In a content-based scientific publication RS, recommendations are composed by observing the features of users and papers. Content-based recommendation encompasses three primary steps, namely, item representation, user modeling, and recommendation generation. A crucial part of generating recommendations is the user modeling process. Nevertheless, this step is often neglected in existing content-based scientific publication RS. Moreover, most existing approaches do not capture the semantics of user models and papers. To address these limitations, in this paper we present a transparent Recommendation and Interest Modeling Application (RIMA), a content-based scientific publication RS that implicitly derives user interest models from their authored papers. To address the semantic issues, RIMA combines word embedding-based keyphrase extraction techniques with knowledge bases to generate semantically-enriched user interest models, and additionally leverages pretrained transformer sentence encoders to represent user models and papers and compute their similarities. The effectiveness of our approach was assessed through an offline evaluation by conducting extensive experiments on various datasets along with user study (N = 22), demonstrating that (a) combining SIFRank and SqueezeBERT as an embedding-based keyphrase extraction method with DBpedia as a knowledge base improved the quality of the user interest modeling step, and (b) using the msmarco-distilbert-base-tas-b sentence transformer model achieved better results in the recommendation generation step. Full article

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18 pages, 373 KiB

Open AccessArticle

Group Leader vs. Remaining Group—Whose Data Should Be Used for Prediction of Team Performance?

by Ronald Böck

Multimodal Technol. Interact. 2023, 7(9), 90; https://doi.org/10.3390/mti7090090 - 14 Sep 2023

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Abstract

Humans are considered to be communicative, usually interacting in dyads or groups. In this paper, we investigate group interactions regarding performance in a rather formal gathering. In particular, a collection of ten performance indicators used in social group sciences is used to assess [...] Read more.

Humans are considered to be communicative, usually interacting in dyads or groups. In this paper, we investigate group interactions regarding performance in a rather formal gathering. In particular, a collection of ten performance indicators used in social group sciences is used to assess the outcomes of the meetings in this manuscript, in an automatic, machine learning-based way. For this, the Parking Lot Corpus, comprising 70 meetings in total, is analysed. At first, we obtain baseline results for the automatic prediction of performance results on the corpus. This is the first time the Parking Lot Corpus is tapped in this sense. Additionally, we compare baseline values to those obtained, utilising bidirectional long-short term memories. For multiple performance indicators, improvements in the baseline results are able to be achieved. Furthermore, the experiments showed a trend that the acoustic material of the remaining group should use for the prediction of team performance. Full article

(This article belongs to the Special Issue Feature Papers in Multimodal Technologies and Interaction—Edition 2023)

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18 pages, 6214 KiB

Open AccessArticle

An Investigation of the Use of Augmented Reality in Public Art

by Tamlyn Young and Mark T. Marshall

Multimodal Technol. Interact. 2023, 7(9), 89; https://doi.org/10.3390/mti7090089 - 11 Sep 2023

Viewed by 1978

Abstract

Augmented reality offers many artistic possibilities when it comes to the creation of place-based public artworks. In this paper, we present a series of works around the topic of augmented reality (AR) art and place-based storytelling, including the use of walking as a [...] Read more.

Augmented reality offers many artistic possibilities when it comes to the creation of place-based public artworks. In this paper, we present a series of works around the topic of augmented reality (AR) art and place-based storytelling, including the use of walking as a creative method, a series of workshops with emerging artists, public AR art collaborations and a study to examine user experience when interacting with such artworks. Our findings from these works show the potential of integrating augmented reality with public physical artworks and offer guidance to artists and AR developers on how to expand this potential. For artists, we show the importance of the space in which the artwork will be placed and provide guidance on how to work with the space. For developers, we find that there is a need to create tools that work with artists’ existing practices and to investigate how to expand augmented reality past the limitations of site- or piece-specific apps. Full article

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18 pages, 258 KiB

Open AccessArticle

Challenges in Virtual Reality Training for CBRN Events

by Georg Regal, Daniele Pretolesi, Helmut Schrom-Feiertag, Jaison Puthenkalam, Massimo Migliorini, Elios De Maio, Francesca Scarrone, Marina Nadalin, Massimiliano Guarneri, Grace P. Xerri, Daniele Di Giovanni, Paola Tessari, Federica Genna, Andrea D’Angelo and Markus Murtinger

Multimodal Technol. Interact. 2023, 7(9), 88; https://doi.org/10.3390/mti7090088 - 11 Sep 2023

Cited by 2 | Viewed by 2400

Abstract

The contemporary geopolitical environment and strategic uncertainty shaped by asymmetric and hybrid threats urge the future development of hands-on training in realistic environments. Training in immersive, virtual environments is a promising approach. Immersive training can support training for contexts that are otherwise hard [...] Read more.

The contemporary geopolitical environment and strategic uncertainty shaped by asymmetric and hybrid threats urge the future development of hands-on training in realistic environments. Training in immersive, virtual environments is a promising approach. Immersive training can support training for contexts that are otherwise hard to access, dangerous, or have high costs. This paper discusses the challenges for virtual reality training in the CBRN (chemical, biological, radioactive, nuclear) domain. Based on initial considerations and a literature review, we conducted a survey and three workshops to gather requirements for CBRN training in virtual environments. We structured the gathered insights into four overarching themes—the future of CBRN training, ethical and safety requirements, evaluation and feedback, and tangible objects and tools. We provide insights on these four themes and discuss recommendations. Full article

(This article belongs to the Special Issue Designing EdTech and Virtual Learning Environments)

24 pages, 2376 KiB

Open AccessArticle

Augmented Reality in Portuguese Museums: A Grounded Theory Study on the Museum Professionals’ Perspectives

by Natacha Fernandes and Joana Casteleiro-Pitrez

Multimodal Technol. Interact. 2023, 7(9), 87; https://doi.org/10.3390/mti7090087 - 11 Sep 2023

Viewed by 1427

Abstract

Augmented Reality (AR) is increasingly present in several fields, including the museological space, where the challenges of presenting objects interactively and attractively are constant, especially with the sociocultural changes of recent decades. Although there are numerous studies on AR in museums, the perspective [...] Read more.

Augmented Reality (AR) is increasingly present in several fields, including the museological space, where the challenges of presenting objects interactively and attractively are constant, especially with the sociocultural changes of recent decades. Although there are numerous studies on AR in museums, the perspective of museum professionals on the technology still needs to be explored. Thus, in this study, we use a qualitative design and conduct in-depth interviews with professionals from 10 Portuguese museums involved in creating or applying AR within these environments. Applying the grounded theory, the researchers propose a framework to understand Portuguese museum professionals’ practices, perceptions, and experiences with AR in museum environments. The findings allow the creation of a theoretical framework divided into four levels, namely the perceptions of museum professionals on the role and use of AR, the understanding of departments, museum teams, and digital strategies, the perceived challenges, limitations, and advantages in the use of augmented reality technologies, and the future perspectives of AR in museums. The theory resulting from this study may also contribute suggestions for the design and implementation of AR in museums, which both museum professionals and designers can use. Full article

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26 pages, 18928 KiB

Open AccessArticle

A Comparative Analysis of Low or No-Code Authoring Tools for Location-Based Games

by Christos Batsaras and Stelios Xinogalos

Multimodal Technol. Interact. 2023, 7(9), 86; https://doi.org/10.3390/mti7090086 - 01 Sep 2023

Viewed by 1377

Abstract

This article presents a comparative analysis of four low or no-code location-based game (LBG) authoring tools, namely Taleblazer, Aris, Actionbound, and Locatify. Each tool is examined in detail, with an emphasis on the functions and capabilities it provides for the development of LBGs. [...] Read more.

This article presents a comparative analysis of four low or no-code location-based game (LBG) authoring tools, namely Taleblazer, Aris, Actionbound, and Locatify. Each tool is examined in detail, with an emphasis on the functions and capabilities it provides for the development of LBGs. The article builds on the history and purpose of LBGs, their characteristics, as well as basic concepts and previous applications, placing emphasis both on the technological and pedagogical dimensions of these games. The evaluation of the tools is based on certain criteria, or metrics, recorded in the literature and empirical data collected through the development of prototype games for each tool. The tools are comparatively analyzed in terms of the LBG’s constituent features they incorporate, the fundamental and additional functionality provided to the developer, as well as the existence or absence of features that captivate players in the game experience. Moreover, feedback is provided based on the practical use of the platforms for developing LBGs in order to support prospective developers in making an informed choice of an LBG platform for implementing a specific game. The games were created by taking advantage of as many features of the tools as possible in order to have a more fair and complete evaluation. This study aims to highlight the affordances and limitations of the investigated low or no-code LBG authoring tools, enabling anyone interested in developing an LBG to choose the most appropriate tool taking into account their needs and technological background or designing their own LBG authoring tools. Full article

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14 pages, 9716 KiB

Open AccessArticle

Can You Dance? A Study of Child–Robot Interaction and Emotional Response Using the NAO Robot

by Vid Podpečan

Multimodal Technol. Interact. 2023, 7(9), 85; https://doi.org/10.3390/mti7090085 - 30 Aug 2023

Cited by 1 | Viewed by 1543

Abstract

This retrospective study presents and summarizes our long-term efforts in the popularization of robotics, engineering, and artificial intelligence (STEM) using the NAO humanoid robot. By a conservative estimate, over a span of 8 years, we engaged at least a couple of thousand participants: [...] Read more.

This retrospective study presents and summarizes our long-term efforts in the popularization of robotics, engineering, and artificial intelligence (STEM) using the NAO humanoid robot. By a conservative estimate, over a span of 8 years, we engaged at least a couple of thousand participants: approximately 70% were preschool children, 15% were elementary school students, and 15% were teenagers and adults. We describe several robot applications that were developed specifically for this task and assess their qualitative performance outside a controlled research setting, catering to various demographics, including those with special needs (ASD, ADHD). Five groups of applications are presented: (1) motor development activities and games, (2) children’s games, (3) theatrical performances, (4) artificial intelligence applications, and (5) data harvesting applications. Different cases of human–robot interactions are considered and evaluated according to our experience, and we discuss their weak points and potential improvements. We examine the response of the audience when confronted with a humanoid robot featuring intelligent behavior, such as conversational intelligence and emotion recognition. We consider the importance of the robot’s physical appearance, the emotional dynamics of human–robot engagement across age groups, the relevance of non-verbal cues, and analyze drawings crafted by preschool children both before and after their interaction with the NAO robot. Full article

(This article belongs to the Special Issue Intricacies of Child–Robot Interaction - 2nd Edition)

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Multimodal Technol. Interact., Volume 7, Issue 9 (September 2023) – 8 articles

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