@article{hojjati_training_2025,

title = {Training for Defense: Satellite Events, held together with the 20th International Conference on Persuasive Technology, PERSUASIVE 2025},

author = {A. Hojjati and J. Ham},

editor = {I. Wiafe, A. Babiker, J. Ham, K. Oyibo, E. Vlahu-Gjorgievska},

url = {https://www.scopus.com/pages/publications/105011937417},

doi = {10.1007/978-3-031-97177-8_2},

issn = {978-3-031-97176-1},

year  = {2025},

date = {2025-07-01},

urldate = {2025-07-01},

journal = {Persuasive Technology. PERSUASIVE 2025 Satellite Events},

pages = {18–31},

series = {Communications in Computer and Information Science (CCIS)},

abstract = {Phishing can cause severe security breaches and its frequency and diversity has rapidly increased. Current countermeasures consist mostly of training users in identifying phishing emails by their appearance. However, we argue that in the long run the effect of such trainings will be limited because phishers rapidly evolve their email design and this makes phishing attacks unrecognizable. Still, phishing emails have a universal characteristic: They attempt to influence the users to perform certain behaviors using influencing strategies. Thus, we argue that training users in recognizing the influencing strategies used by technology helps them to defend themselves against (even very advanced, visually unrecognizable) phishing emails. In this study, we randomly assigned 151 participants to two groups (trained on influencing strategies vs. trained on the history of emails). Our learning material was a six-minute training video. After watching the video, participants were presented with a series of emails that contained influencing strategies. These emails were followed by questions about recognition of influencing strategies and the user’s behavioral intentions towards the email. Results provided no evidence that a participant’s intension of clicking on links was influenced by the influencing strategy training video. Importantly, results did show that participants who had watched the influencing strategy training video, correctly recognized more influencing strategies in emails. Also, participants who recognized the use of manipulation techniques in emails, intended to click on less links. These results open a new line of defense against persuasive technology: harnessing users by training them in influencing strategy recognition.},

note = {Place: Cham 

Publisher: Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ghazali_social_2025,

title = {Social Robots as Decision-Making Companions: Exploring the Impact of Social Cues on Human Responses},

author = {A. S. Ghazali and H. Hafizalshah and S. N. Sidek and H. M. Yusof and J. Ham},

url = {https://www.scopus.com/pages/publications/105005606083},

doi = {10.1142/S0219843625500021},

issn = {0219-8436},

year  = {2025},

date = {2025-06-01},

urldate = {2025-06-01},

journal = {International Journal of Humanoid Robotics},

volume = {22},

number = {3},

abstract = {Making decisions, particularly ones fraught with ambiguity, inherently induces stress, which is a recognized contributor to long-term mental health issues. In high-stakes or uncertain environments, stress can significantly impair decision quality and well-being. Social robots offer a promising solution by potentially providing companionship and cognitive assistance in such scenarios. This study investigates the influence of verbal social cues used by social robots on human responses. In a laboratory setting, 60 participants interacted with the Alpha Mini robot, a programmable social agent, for 30min. The robot offered advice using combinations of controlling language (high versus low) and social praise (absent versus present) in a between-subject design setup while playing a decision-making computer game. Post-interaction, social responses were measured using questionnaires. Results revealed strong, positive correlations between participants’ enjoyment of interacting with the robot and their intention to use it again in the future, as well as their liking and trust in the robot’s advice. These correlations were statistically significant (p<0.01) and suggest that positive user experiences can translate into continued engagement. Positive responses were observed regardless of the specific social cues employed. To design effective human–robot interactions (HRI), multiple social cues should be integrated using high controlling language for clarity and direction paired with social praise to soften the tone in order to enhance trust, enjoyment, and effectiveness. Future work might enhance the current findings by integrating physiological data into the measures used to assess emotional responses to the robot and its cues. Additionally, expanding participant demographics and incorporating longitudinal studies could further validate and extend these results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chen_effects_2025,

title = {Effects of Chatbots with Anthropomorphic Visual and Auditory Cues on Users’ Affective Preference: Evidence from Event-Related Potentials},

author = {J. Chen and F. Guo and Z. Zhang and X. Tian and J. Ham},

url = {https://www.scopus.com/pages/publications/105005849554},

doi = {10.1080/10447318.2025.2499169},

issn = {1044-7318},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-01},

journal = {International Journal of Human-Computer Interaction},

volume = {XX},

abstract = {Anthropomorphic visual and auditory cues are two crucial design elements influencing users’ affective preference for chatbots. However, most earlier studies only focused on one of them and it is still unknown how anthropomorphic visual appearance and voice influence users’ affective preference and neural responses. In the current research, participants’ subjective preference evaluation and objective ERP responses were measured when being presented with chatbots with different visual and auditory cues. (human-like voice and mechanical voice). Subjective results indicated that consistent cues of anthropomorphic visual appearances and voices jointly evoked users’ higher affective preference for chatbots. Notably, auditory cues play a dominant role among audiovisual cues that influence users’ affective preference for chatbots. ERP results showed that low anthropomorphic visual appearances and mechanical voices jointly elicited larger P2 and P3. Additionally, chatbots with low anthropomorphic visual appearances and chatbots with human-like voices elicited larger LPP. These findings hold theoretic implications for understanding the impact of chatbots’ visual appearance and voice on users’ affective preference and provide practical insights for the design of human-chatbot interactions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{koranteng_impact_2025,

title = {The Impact of Social Support Strategies on Users’ Credibility Perceptions and Continuous Use Intentions of Academic Social Networking Sites: An Empirical Study},

author = {F. N. Koranteng and U. Matzat and I. Wiafe and J. Ham},

url = {https://www.scopus.com/pages/publications/105005531224},

doi = {10.1080/10447318.2025.2495121},

issn = {1044-7318},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-01},

journal = {International Journal of Human-Computer Interaction},

volume = {XX},

abstract = {With rapid digital innovation, social support strategies are increasingly embedded in Academic Social Networking Sites (ASNSs) to shape user perceptions and behaviors. However, limited empirical research has examined how these strategies influence users’ credibility perceptions and behavioral intentions. Credibility, a key factor driving participation on ASNSs, remains underexplored in this context. This study investigates the role of seven social support strategies within the Persuasive System Design (PSD) framework. It examines their effect on credibility perceptions, as well as the effects of credibility on perceived persuasiveness and continuous use intentions. Using data from 255 ASNS users and Partial Least Squares Structural Equation Modeling (PLS-SEM), results show that several social support strategies significantly shape perceived social learning, which strongly influences credibility perceptions. Additionally, perceived persuasiveness mediates the relationship between perceived credibility and continuous use intention. The findings offer practical insights for designing ASNSs that enhance credibility, persuasiveness, and sustained engagement.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{loman_robustness_2025,

title = {Robustness Measures for Stochastic Parallel Machine Scheduling and Train Unit Shunting: Rail Dresden 2025},

author = {C. Loman and L. Pascual and M. Akker and R. Broek and H. Hoogeveen},

year  = {2025},

date = {2025-03-01},

urldate = {2025-03-01},

journal = {Robustness Measures for Stochastic Parallel Machine Scheduling and Train Unit Shunting},

abstract = {In this paper, we investigate measures that can give us information about the robustness for complex scheduling problems. We identify 14 robustness measures from the literature, as well as introduce 4 new ones. We then use simulation to investigate how well these robustness measures correlate with the stability of the objective function under disturbances (quality robustness), and with the stability of the schedule itself (solution robustness). We first do this in the context of Parallel Machine Scheduling, which is a very general setting that is comparable to many practical situations. We then take the results from that investigation and use the best performing measures as objectives in a local search for the Train Unit Shunting Problem with Service Scheduling. We investigate which of these measures give us a better quality robustness, and which measures give us a better solution robustness. We look at how these measures perform under different ways of inserting slacks into the schedule. We show how the performance of the measures can differ in these different cases, and conclude with what we believe to be a good set of robustness measures to consider for any scheduling problem.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{li_audiovisual_2025,

title = {Audiovisual Affective Design of Humanoid Robot Appearance and Voice Based on Kansei Engineering},

author = {M. Li and J. Zhang and F. Guo and Y. Liao and X. Hu and J. Ham},

url = {https://www.scopus.com/pages/publications/85217195778},

doi = {10.1007/s12369-024-01202-5},

issn = {1875-4791},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {International Journal of Social Robotics},

volume = {17},

number = {1},

pages = {15–37},

abstract = {Humanoid robots, characterized by their anthropomorphic design, have become increasingly common in various service areas. Nevertheless, the majority of current affective designs of humanoid robots primarily concentrate on the physical appearance while overlooking its (audiovisual) integration with voice. In this study, we propose simultaneously designing the appearance and voice of humanoid robots using Kansei Engineering, an effective method for optimizing the affective design of products. We first selected representative humanoid robots with different appearances and voices and constructed kansei space to capture users’ affective needs for these robots. Then, we decomposed appearances and parameterized voices to extract design features and orthogonalized these design features to generate prototypes. After that, we conducted an evaluation experiment to acquire users’ affective evaluations on the combinations of appearance and voice. Based on the data, relationship models between design features and users’ kansei images and holistic preferences were constructed using the back-propagation neural network. Furthermore, optimization design models were formulated and resolved through the genetic algorithm. Also, we conducted a validation experiment, and the results demonstrated that the optimized design schemes look harmonious in appearance, sound warmth in voice, and achieve a high level of audiovisual compatibility. The results suggest that the proposed approach can effectively optimize the audiovisual affective design of humanoid robot appearance and voice. Moreover, it can not only provide methodological support for the affective design of robots and other voice-based smart products but can also help to improve the affective experience quality and facilitate the application of robots in service areas.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{koranteng_investigating_2025,

title = {Investigating the Effects of Implicit and Explicit Personalization on Perceived Credibility: 13th International Workshop on Behavior Change Support Systems, BCSS 2025},

author = {F. N. Koranteng and I. Wiafe and J. Ham and U. Matzat},

editor = {H. Oinas-Kukkonen, S. Nabwire},

url = {https://www.scopus.com/pages/publications/105006905426},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Behavior Change Support Systems 2025},

pages = {29–42},

series = {CEUR Workshop Proceedings},

abstract = {Personalizing computer systems (such as Academic Social Networking Sites) can improve positive user perceptions, particularly credibility perceptions of that system. Earlier research has identified two broad personalization approaches: Implicit and Explicit personalization. Moreover, applying the wrong personalization approach may negatively affect users' perceptions of the system's credibility. Yet, the evidence that earlier research provides for the relevance and importance of the different personalization approaches on perceived credibility in system design is limited. This study explores which of the two personalization approaches is most important and could be prioritized when designing systems to improve credibility perceptions. Academic Social Networking Sites (ASNSs) users' perceptions of implicit and explicit personalization and system credibility are gathered via survey and analyzed using Partial Least Square Structural Equation Modeling. We find that whereas Implicit personalization has a positive influence, Explicit personalization negatively influences users' credibility perceptions. Furthermore, the Importance Performance Map Analysis (IPMA) reveals implicit personalization as the better-performing and more important approach for promoting credibility perceptions on ASNSs. Based on the results, this study recommends further investigations into how personalizing the personalization approaches for different users may affect their credibility perceptions.},

note = {Publisher: CEUR-WS.org},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{van_erp_online_2024,

title = {Online Structure Learning with Dirichlet Processes Through Message Passing: 5th International Workshop on Active Inference, IWAI 2024},

author = {B. Erp and W. W. L. Nuijten and B. Vries},

editor = {C. L. Buckley and D. Cialfi and P. Lanillos and R. J. Pitliya and N. Sajid and H. Shimazaki and T. Verbelen and M. Wisse},

url = {https://www.scopus.com/pages/publications/85215817803},

doi = {10.1007/978-3-031-77138-5_6},

issn = {978-3-031-77137-8},

year  = {2024},

date = {2024-12-01},

urldate = {2024-12-01},

journal = {Active Inference},

pages = {91–104},

series = {Communications in Computer and Information Science (CCIS)},

abstract = {Generative or probabilistic modeling is crucial for developing intelligent agents that can reason about their environment. However, designing these models manually for complex tasks is often infeasible. Structure learning addresses this challenge by automating model creation based on sensory observations, balancing accuracy with complexity. Central to structure learning is Bayesian model comparison, which provides a principled framework for evaluating models based on their evidence. This paper focuses on model expansion and introduces an online message passing procedure using Dirichlet processes, a prominent prior in non-parametric Bayesian methods. Our approach builds on previous work by automating Bayesian model comparison using message passing based on variational free energy minimization. We derive novel message passing update rules to emulate Dirichlet processes, offering a flexible and scalable method for online structure learning. Our method generalizes to arbitrary models and treats structure learning identically to state estimation and parameter learning. The experimental results validate the effectiveness of our approach on an infinite mixture model.},

note = {Place: Cham 

Publisher: Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dameski_system-phenomenology_2024,

title = {System-phenomenology: An empirical case for collectives in mediation theory},

author = {A. Dameski and A. Spahn and C. A. S. Pouw and R. Kodapanakkal and A. Haans and A. Corbetta and F. Toschi and J. R. C. Ham and G. Bombaerts},

doi = {10.59490/jhtr.2024.2.7031},

issn = {2773-2266},

year  = {2024},

date = {2024-12-01},

urldate = {2024-12-01},

journal = {Journal of Human-Technology Relations},

volume = {2},

number = {7031},

abstract = {Postphenomenology and mediation theory strongly explain the micro-level interactions between human individuals and objects. Recently, humans as a collective have been added to the theory at the political macro-level, which we argue that is an important contribution. However, the enlargement of the theory would also merit a meso-level explanation of the role of collectives, in between the micro- and the macro-level. For this purpose, we introduce the mediation triangle, illustrating three bidirectional relations, all mediated by technology: human-object, human-collective, and collective-object. The mediation triangle we combine with three borrowed concepts from systems philosophy to aid in our framework design: differentiality, emergence, and irreducibility. This approach, named system-phenomenology, can explain the interaction between objects, individuals, collectives, political levels, and technology. We illustrate this using an empirical case of boarding and deboarding at train stations. We conclude that system-phenomenology is promising, but further research is needed to develop this theory conceptually.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chen_different_2024,

title = {Different dimensions of anthropomorphic design cues: How visual appearance and conversational style influence users’ information disclosure tendency towards chatbots},

author = {J. Chen and M. Li and J. Ham},

url = {https://www.sciencedirect.com/science/article/pii/S1071581924001046},

doi = {10.1016/j.ijhcs.2024.103320},

issn = {1071-5819},

year  = {2024},

date = {2024-10-01},

urldate = {2024-10-01},

journal = {International Journal of Human-Computer Studies},

volume = {190},

pages = {103320},

abstract = {Text-based chatbots are widely used to deliver personalized services by leveraging user-provided information, and anthropomorphic design is crucial for their effectiveness. However, most earlier studies investigated the effects of anthropomorphic design of chatbots while manipulating only one dimension of anthropomorphic cues. The current research investigated how different dimensions of anthropomorphic design cues affect users’ information disclosure tendency towards chatbots. That is, the present study examined the effects of visual appearance (high anthropomorphism vs. low anthropomorphism), manipulating the visual cues dimension, and conversational style (human-like vs. mechanical), manipulating the verbal cues dimension, on users’ information disclosure tendency towards chatbots. Results showed positive effects of human-like conversational style on users’ information disclosure tendency. Of particular significance, an interaction effect between visual appearance and conversational style on users’ information disclosure tendency was found. Users reported a higher information disclosure tendency when the chatbot was designed with anthropomorphic cues consistent over dimensions. This finding suggested that an expectancy violation effect occurs when a chatbot exhibits inconsistent anthropomorphic design cues on two different dimensions. Besides, perceived security was identified as a positive mediating factor in the relationship between conversational style and users’ information disclosure tendency. This study advances research on users’ information disclosure tendency towards anthropomorphic chatbots and highlights the importance of different dimensions of anthropomorphic cues in chatbot design. Additionally, practical guidance for chatbot designers was also provided.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tisza_can_2024,

title = {Can Robots Enhance the Learning Experience by Making Music More Fun?: 33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024},

author = {G. Tisza and H. Song and P. Markopoulos and E. I. Barakova and J. Ham},

url = {https://www.scopus.com/pages/publications/85209809226},

doi = {10.1109/RO-MAN60168.2024.10731440},

year  = {2024},

date = {2024-10-01},

urldate = {2024-10-01},

journal = {2024 33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024},

pages = {893–900},

abstract = {Research has shown the potential of social robots to support learning in science, technology, and language. We contribute to this field by exploring how robots can support music learning. We report on a within-subjects experiment where 50 young learners practiced the piano in the presence of a robot assuming a non-evaluative and a self-assessment enhancing role implemented in a Wizard-of-Oz fashion. We examined whether the robot can make piano practice more fun, and whether initiating self-assessment to support self-regulated learning is a useful strategy for the robot. We collected quantitative self-report data to assess fun, learning, interest, engagement, and effort. We found a direct positive effect of fun on learning in the context of musical instrument practice. Path modeling showed a positive influence of having fun on learners' attitudes, interests, and learning outcomes in music education, particularly with the self- assessment robot role exhibiting superiority.},

note = {Publisher: Institute of Electrical and Electronics Engineers},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kodapanakkal_investigating_2024,

title = {Investigating sociophysical attributes underlying train boarding efficiency and their importance for nudging},

author = {R. I. Kodapanakkal and A. Haans and J. Ham and R. J. Giesen and N. D. Güneş and T. M. L. Markink and J. M. Osinga and C. A. S. Pouw and G. Bombaerts and A. Corbetta and A. Dameski and A. Spahn and F. Toschi},

url = {https://www.scopus.com/pages/publications/85196111014},

doi = {10.1016/j.ssci.2024.106568},

issn = {0925-7535},

year  = {2024},

date = {2024-09-01},

urldate = {2024-09-01},

journal = {Safety Science},

volume = {177},

number = {106568},

abstract = {Nudging has become a popular method to change the behavior of pedestrians in public spaces. However, nudges often do not work as intended because they are based on an incomplete understanding of the nudging environment, physical (e.g., pedestrian trajectories), but not psychological data is used in their development, and behavioral theories are often inadequate or not (correctly) applied. In this article, we argue that the design of nudges can benefit from complementary psychological data analyzed using relevant social and environmental psychological theories. Adequate theories, we argue, are those that aim at describing the objective (i.e., person independent) attributes of the environment or situation and how these affect human decision-making. Using the example of train boarding, and in particular the formation of the deboarding corridor, we demonstrate how psychological theories like interdependence theory and social norms theory can be applied to relevant psychological data—in our case obtained with two focus groups—to better characterize the sociophysical attributes of the train boarding situation. The focus group, or sometimes called a “group discussion”, is a qualitative research method in which data is generated from guided discussions amongst research participants following pre-defined discussion topics. Based on the thematic analysis of the focus group data, we find that a high level of competition and interdependence are related to structural aspects of the train boarding situation. Subsequently, we use these insights to provide tentative explanations for, or hypotheses about micro- and macroscopic behavior patterns observed during train boarding. Finally, we discuss how these insights, in turn, can inform the design of nudges that can be further investigated in future research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ruijten_serious_2024,

title = {A serious game for promoting sustainable food choices: 19th International Conference on Persuasive Technology Adjunct, PERSUASIVE-ADJ 2024},

author = {P. A. M. Ruijten and J. Ham and N. Jongh},

editor = {K. Oyibo, W. Xu, E. Vlahu-Gjorgievska},

url = {https://www.scopus.com/pages/publications/85199647853},

year  = {2024},

date = {2024-07-01},

urldate = {2024-07-01},

journal = {Persuasive 2024 Adjunct Proceedings (PERSUASIVE-ADJ 2024)},

pages = {110–111},

series = {CEUR Workshop Proceedings},

abstract = {A type of persuasive technology that has gained popularity over the last decade is gamification. We aimed to influence people’s sustainable food choices by letting them buy ingredients for a dish in two Virtual Reality supermarkets; a gamified one and a regular one. In the gamified supermarket, a point system was added to all the ingredients that could be bought. Also, we used olfactory feedback to enhance the effect of gamification. Results showed an effect of gamification on people’s behavior during the experiment, as well as their self-reported food choices in the week after the experiment. Implications of these findings are discussed in light of how we can persuade people into making healthy and sustainable food choices.},

note = {Publisher: CEUR-WS.org},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ruijten_how_2024,

title = {How the Role of a Persuasive Robot Impacts One’s Attitude Towards It: 19th International Conference on Persuasive Technology, PERSUASIVE 2024},

author = {P. A. M. Ruijten and J. Smeding and J. Ham},

editor = {N. Baghaei, R. Ali, K. Win, K. Oyibo},

url = {https://www.scopus.com/pages/publications/85192167388},

doi = {10.1007/978-3-031-58226-4_19},

issn = {978-3-031-58225-7},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-01},

journal = {Persuasive Technology},

pages = {252–261},

series = {Lecture Notes in Computer Science (LNCS)},

abstract = {Recent years have seen a development of social robots in all kinds of different roles. For social robots to be tailored to the needs of the user and become more accepted, we need to understand how people perceive and interact with robots in these different roles. This study investigates people’s attitudes toward robots in two different roles (utilitarian: practically oriented vs hedonic: socially oriented) after interacting with them at home for several days. Results show that people’s attitudes towards the same robot differ between the roles that were applied to the robot. People also described their interactions with the robot in different terms depending on its role. Implications of these findings are discussed in light of tailored approaches in the design of interactions between humans and social robots.},

note = {Place: Cham 

Publisher: Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chen_effects_2024,

title = {Effects of Anthropomorphic Design Cues of Chatbots on Users’ Perception and Visual Behaviors},

author = {J. Chen and F. Guo and Z. Ren and M. Li and J. Ham},

url = {https://www.scopus.com/pages/publications/85152381313},

doi = {10.1080/10447318.2023.2193514},

issn = {1044-7318},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {International Journal of Human-Computer Interaction},

volume = {40},

number = {14},

pages = {3636–3654},

abstract = {Measurement of users’ perception and visual behaviors to anthropomorphic design cues of chatbots can improve our understanding of chatbots and potentially optimize chatbot design. However, as two typical and basic features, how chatbot appearances and conversational styles jointly affect users’ perception and visual behaviors remains unclear. Therefore, this study conducted an eye-tracking experiment to explore users’ perception and visual behaviors. Results indicate that anthropomorphic appearances and human-like conversational styles jointly increased users’ perception of chatbots’ social presence, trust in chatbots, and satisfaction with chatbots. In contrast, on users’ visual behaviors, such a joint effect was not found, although chatbots with higher anthropomorphic appearances and human-like conversational styles triggered more fixation counts and longer dwell time. These findings suggest that anthropomorphic appearance and human-like conversational style can improve users’ perception and attract more visual attention to chatbots. These findings provide theoretical contributions and practical implications for relevant researchers and designers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kodapanakkal_psychological_2024,

title = {A psychological approach to understanding microscopic and macroscopic structures during train boarding processes: International Conference on Traffic and Granular Flow, TGF 2022},

author = {R. I. Kodapanakkal and C. A. S. Pouw and G. Bombaerts and A. Corbetta and A. Dameski and A. Haans and J. Ham and A. Spahn and F. Toschi},

editor = {K. R. Rao and A. Seyfried and A. Schadschneider},

url = {https://www.scopus.com/pages/publications/85197268348},

doi = {10.1007/978-981-99-7976-9_28},

issn = {9789819979752},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Traffic and Granular Flow'22},

pages = {223–230},

series = {Lecture Notes in Civil Engineering},

abstract = {Current research on the train boarding process focuses predominantly on the physical modelling of pedestrian dynamics and situational characteristics such as platform design. Little psychology is involved in this approach even though individual behavior is a major factor in influencing dwell times. We take a systematic psychological approach to estimate whether parameters like pedestrian speed, area available per pedestrian, and interpersonal distance show variation at the microscopic level (individual variation), macroscopic level (situational variation), or both. Analyzing real-life train (de)boarding events (n = 3728) at a specific location at a Dutch train station, we find that boarders’ speed varies more at the microscopic (individual variation) than the macroscopic level. This behavior could thus result from stable aspects of the situation such as some structural feature of the environment or a social norm. Understanding such variation is helpful in designing behavioral interventions/nudges. If variation is due to individual differences, then an individual-targeted intervention will be most effective. If variation is due to situational differences, then individual-targeted interventions may not be particularly useful, and nudges targeted at crowds or environmental features may be most effective.},

note = {Publisher: Springer},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{song_impact_2024,

title = {The impact of social robots' presence and roles on children's performance in musical instrument practice},

author = {H. Song and E. I. Barakova and J. Ham and P. Markopoulos},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/bjet.13416},

doi = {10.1111/bjet.13416},

issn = {1467-8535},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {British Journal of Educational Technology},

volume = {55},

number = {3},

pages = {1041–1059},

abstract = {Research on the educational applications of social robots has shown how they can motivate children and help improve academic learning outcomes. Here, we examine how robots can support skill learning and, more specifically, musical instrument practice. Drawing from social facilitation theory and evaluation apprehension theory we expected that the robot's mere presence would impact children's performance and that this effect would be contingent upon the children expecting the robot to evaluate their performance. We report an experiment with children (N = 31) aged nine to twelve who practiced a familiar and new piece alone, in the presence of an evaluative robot, and in the presence of a non-evaluative robot. We found that children performed better in terms of rhythm, pitch, and general impression in the presence of the non-evaluative robot. These findings offer important insights for designing robot tutors for music learning. Practitioner notes What is already known about this topic Social robots have been applied in different educational scenarios (e.g., second language, math, and programming) and were proven to be beneficial for children's motivation. Musical instrument learning requires practice, perseverance, and social support to become successful. Social robots can be used as a provider of social support during musical instrument practice. Children tend to perform better on easy or well-rehearsed tasks and worse on complex tasks or new ones with the presence of observers, but only when they believe the observer can evaluate them. What this paper adds Social robots are beneficial for children's performance in musical instrument learning. Limited evidence was found to prove that children tend to perform better on old melodies and worse on new melodies in the presence of a social robot. However, the results confirmed that the level of evaluative of the robot matters. Children tend to have better performance with the robot that did not provide evaluative comments when practicing a new melody (a difficult task) than alone and with the robot that offered evaluative comments. This study confirmed that social robots can provide support to children in practicing music, helping to improve their performance. Implications for practice and/or policy Social facilitation and evaluation apprehension effects need to be taken into consideration during the behaviour design of companion robots in learning scenarios. Robots, which were intended to motivate children in learning, should be designed to not provide evaluative comments.},

note = {_eprint: https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13416},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kodapanakkal_influence_2023,

title = {The Influence of Macroscopic Pedestrian Structures on Train Boarding Efficiency},

author = {R. Kodapanakkal and C. A. S. Pouw and A. Haans and J. R. C. Ham and G. Bombaerts and A. Corbetta and A. Dameski and A. Spahn and F. Toschi},

url = {https://arxiv.org/abs/2309.05476},

doi = {10.48550/arXiv.2309.05476},

year  = {2023},

date = {2023-09-01},

urldate = {2023-09-01},

journal = {The Influence of Macroscopic Pedestrian Structures on Train Boarding Efficiency},

volume = {2309.05476},

pages = {1–27},

abstract = {A deeper understanding of pedestrian dynamics is essential to improve crowd flows in public spaces such as train stations. It is essential to understand both the physical and the psychological processes present in this context. However, current research on train boarding behavior is limited in scope and mainly focuses on how group level variables such as number of boarders/deboarders influence train boarding efficiency. Viewing pedestrian dynamics through a psychological lens is important for a detailed understanding of the train boarding context and to recognize target areas for improving crowd flows. At Dutch train stations, boarders follow a social norm of waiting at the train door until deboarding is complete. Although people generally adhere to this norm, the way it is executed may not be optimal for deboarding efficiency. We investigate how waiting boarders form a deboarding channel (a corridor where deboarders exit the train) which is a macroscopic structure formed by pedestrians, and how this channel in turn influences the efficiency of deboarding. Analyzing a dataset with 3278 boarding events at Utrecht Centraal Station in the Netherlands from 2017 - 2020 (a subset of a trajectory dataset that captures 100,000 trajectories per day), we found that higher numbers of boarders and a higher ratio of boarders to deboarders, reduced the width of the deboarding channel, and a lower width was associated with lower deboarding efficiency. These results shift the focus from group level variables to identifying macroscopic structures that are formed when pedestrians interact within a social system and provide specific target areas where nudges/behavioral interventions could be implemented.},

note = {Publisher: arXiv.org},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{oyibo_adaptive_2023,

title = {Adaptive and Personalized Persuasive Technologies (ADAPPT 2023) Workshop: 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2023},

author = {K. Oyibo and I. Adaji and R. Orji and J. Ham and J. Vassileva},

url = {https://www.scopus.com/pages/publications/85163702688},

doi = {10.1145/3563359.3595626},

year  = {2023},

date = {2023-06-01},

urldate = {2023-06-01},

journal = {UMAP '23 Adjunct},

pages = {121–122},

abstract = {The Adaptive and Personalized Persuasive Technologies (ADAPPT'23) workshop holding in Cyprus this year is the third edition of the ADAPPT series, which commenced in 2019. The workshop is organized in conjunction with the 31st Association for Computer Machinery (ACM) Conference on User Modeling, Adaptation and Personalization (UMAP). In this preface to the third edition, we summarize the papers accepted for publication in the adjunct proceedings. Finally, we present a list of the members of the organizing and program committees that made the workshop a success.},

note = {Publisher: Association for Computing Machinery, Inc.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{song_how_2023,

title = {‘How Would you Score Yourself?’: The Effect of Self-assessment Strategy Through Robots on Children’s Motivation and Performance in Piano Practice},

author = {H. Song and K. Tsiakas and J. Ham and P. Markopoulos and E. I. Brakova},

url = {http://www.scopus.com/inward/record.url?scp=85180207523&partnerID=8YFLogxK},

doi = {10.1007/s12369-023-01080-3},

issn = {1875-4791},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {International Journal of Social Robotics},

volume = {16},

number = {2},

pages = {327–340},

abstract = {This research examines how to design social robots to support self-regulated learning skills for piano practice. More specifically, a social robot is used to provide feedback to children and initiate self-assessment. To assess the impact of this approach on children’s motivation and performance, we conducted an experiment in a music school where 50 children practiced with both a self-assessment and a non-evaluative robot. Results showed that when the children interacted with the self-assessment robot they had higher motivation and better performance than when they interacted with the non-evaluative robot. Furthermore, interaction effects were found between the robot conditions, the children’s learning stages, and their gender regarding their motivation and rhythm performance. Overall, the study demonstrates a positive influence of robot-initiated self-assessment on children’s musical instrument practice and provided insights for personalized child-robot interaction design.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}