The Cognitive Mechanisms of the Positivity Reactivity Effect on Word Recognition Memory.

A variety of letter string representations has been proposed in the reading literature to account for empirically established orthographic similarity effects from masked priming studies. However, these similarity effects have not been explored in episodic memory paradigms and very few memory models have employed orthographic representation of words. In the current work, through two recognition memory experiments employing word and pseudoword stimuli respectively, we empirically established a set of key orthographic similarity effects for the first time in recognition memory – namely the substitution effect, transposition effect and reverse effect in recognition memory of words and pseudowords, and a start-letter importance in recognition memory of words. Subsequently, we compared orthographic representations from the reading literature including slot coding, closed-bigram, open-bigram and the overlap model. Each of these representations was situated in a global matching model and fitted to recognition performance via Luce’s choice rule in a hierarchical Bayesian framework. Model selection results showed support for the open-bigram representation in both experiments.

The last several years have seen a strong growth of telerobotic technologies with promising implications for many areas of learning. HCI has contributed to these discussions, mainly with studies on user experiences and user interfaces of telepresence robots. However, only a few telerobot studies have addressed everyday use in real-world learning environments. In the post-COVID 19 world, sociotechnical uncertainties and unforeseen challenges to learning in hybrid learning environments constitute a unique frontier where robotic and immersive technologies can mediate learning experiences. The aim of this workshop is to set the stage for a new wave of HCI research that accounts for and begins to develop new insights, concepts, and methods for use of immersive and telerobotic technologies in real-world learning environments. Participants are invited to collaboratively define an HCI research agenda focused on robot-mediated learning in the wild, which will require examining end-user engagements and questioning underlying concepts regarding telerobots for learning.

Recently, an eye-tracking study found that Complexity and other R-PAS variables located in the Engagement and Cognitive Processing domain correlated with a proxy marker for cognitive effort and engagement. The goal of the current study was to test the robustness and validity of those eye-tracking findings by inspecting fMRI data. We hypothesized that the greater the level of engagement and cognitive effort put in place by a Rorschach test-taker, the greater the engagement of his/her cortical areas reflecting ongoing top-down attentional processes should be. We re-analyzed archival fMRI data from 26 healthy participants exposed to the Rorschach inkblots with the instruction to think of what they might be. The association of various Engagement and Cognitive Processing R-PAS scores to increased BOLD signals in the Dorsal Attention Network of the brain was examined. As expected, Complexity showed the strongest effect size across all R-PAS variables under investigation (d = 0.43), followed by Synthesis (d = 0.32) and Human Movement (d = 0.21). Noteworthy, the correlation between the effect sizes found in the current fMRI study and those found in the previously published eye-tracking study consists of an impressive r = .80.

As artificial intelligence (AI) becomes increasingly embedded in knowledge-intensive work, concerns are growing about its psychological impact on employees. While much of the existing literature emphasizes productivity gains and task automation, this study explores a less visible dimension: the potential motivational side effects of AI integration. Specifically, we investigate how the use of AI tools in professional contexts may affect perceived social presence, cognitive effort, motivation, and ultimately, task performance.Grounded in the High-Performance Cycle (Locke & Latham, 2002) and complemented by theories of social presence, perceptual fluency, and cognitive engagement, we develop a comprehensive mediation model. The model hypothesizes that AI usage may reduce motivation indirectly through decreased perceptions of social presence and lower cognitive investment in tasks. Motivation, in turn, is expected to predict self-reported performance outcomes. We further examine whether technological self-efficacy moderates these pathways.To empirically test our model, we conducted a cross-sectional survey with 297 professionals who regularly use AI systems such as generative language models, automation platforms, and AI-driven analytics tools. Participants were recruited via professional networks (e.g., LinkedIn, Prolific Academic) and selected based on their experience with AI in daily work tasks. All key variables - AI usage, perceived social presence, cognitive effort, motivation, and performance - were measured using validated Likert-scale instruments. Data were analyzed using structural equation modeling (SEM) and bootstrapped mediation tests.Results reveal that AI usage has a statistically significant negative effect on both social presence (β = -0.42) and cognitive effort (β = -0.38), which in turn positively influence motivation (β = 0.35 and β = 0.31, respectively). Motivation emerged as the strongest predictor of performance (β = 0.58). Mediation analyses confirmed that the effects of AI on performance are fully mediated by motivational and perceptual variables. Additionally, exploratory moderation analyses showed that technological self-efficacy buffers the negative impact of AI usage on motivation, suggesting individual resilience factors play a role.This study contributes to the literature by extending motivational theories into AI-mediated work contexts and identifying key psychological mechanisms behind technology-induced disengagement. It highlights that AI systems, while operationally efficient, may alter the subjective experience of work in ways that reduce intrinsic engagement. The findings have implications for organizational design, system architecture, and human-AI interaction strategies. They also call for the development of motivationally aware AI systems and for training programs that enhance technological self-efficacy.In sum, our results underscore that the impact of AI is not only functional but also psychological. The future of work will depend not just on how well machines perform, but on how well they preserve the human motivation to engage, create, and perform.

IntroductionRetrieval practice enhances adults' long-term memory over restudying. However, it is less clear whether young children also benefit from retrieval practice. This study assessed whether retrieval practice could support children's novel word learning in the context of storybook reading.MethodIn Experiments 1–3, preschoolers (N = 167, RangeAge = 26–68 months) were presented with 10 novel word-object pairs across four consecutive storybook readings. Half of the children were read the storybook four times (i.e., SSSS), whereas the other half of the children were read the storybook once and were then asked to retrieve the novel words during the subsequent three readings (i.e., STTT). Children's recall and recognition memory for the novel words was tested after a 5-min delay.Results and discussionResults revealed that although children had high retrieval success during learning, retrieval practice did not provide an advantage over re-reading for children's recall (Experiment 1), even when additional mapping and retrieval opportunities were provided (Experiment 2); that is, children who engaged in retrieval practice did not outperform children who re-read the storybooks. A retrieval practice effect also did not emerge in children's recognition memory of novel words (Experiment 3). Taken together, this study suggests that retrieval practice may only benefit young children under specific learning conditions. Future research should therefore consider characteristics of the learner and broader learning context to explain developmental differences in retrieval practice effects.

The effects of social anxiety on recognition memory for social threat words: An ERP study

The proliferation of videos with educational purposes on social media offers unprecedented opportunities for informal learning in virtual space. Yet, research on learner engagement with educational videos in informal learning on social media has been scarce, despite its central role in learning. This study addresses this research gap. Specifically, we investigate how signalling mechanisms (signals and anchors) affect cognitive engagement. We sample YouTube educational videos and analyse the effects of signals and anchors on cognitive engagement on Reddit. Our analyses show that different signals and anchors affect cognitive engagement differently. Textual signals positively associate with cognitive engagement, while visual signals do not. Mathematical models are negatively related to cognitive engagement, and physical models are not correlated with cognitive engagement significantly. Our findings provide valuable empirical knowledge on cognitive engagement with educational videos on social media. This study enriches the understanding of signalling mechanisms and extends the literature on educational videos and multimedia learning. It is also beneficial for video designers and developers to optimise cognitive engagement with the appropriate use of signals and anchors and make online experiences more engaging.

This study aims to understand the symbolic communication process between teachers and hearing-Impaired students at SKH Negeri 01 Serang City, particularly in building message comprehension, self-identity, social interaction, and social behavior through nonverbal symbols such as BISINDO (Indonesian Sign Language), facial expressions, and body movements. This qualitative study evaluates communication between teachers and hearing-Impaired students at SKH Negeri 01 Serang City within a constructivist paradigm using George Herbert Mead's symbolic interactionism. The research employs a qualitative method to observe and assess interactions between teachers and hearing-Impaired students, specifically examining nonverbal communication, facial expressions, and body movements as symbolic forms that facilitate understanding, identity formation, and social behavior. Data were collected through in-depth interviews, participant observation, and documentation involving two teachers and five high school-level hearing-Impaired students. The study finds that hearing-Impaired students construct understanding through their interpretation of nonverbal symbols such as BISINDO, facial expressions, and body movements, demonstrating cognitive (mental) engagement. Observations revealed that when the teacher asked, "What did you learn last week?" Rizky simply frowned and raised his hands, as if he didn't know. He wasn't just thinking internally, but also demonstrating his thought process through nonverbal symbols that others could observe. This action reflects Rizky's active understanding of the teacher's question. These interactions enable students to build self-identification, as evidenced by confidence and self-identity, while fostering social interaction and social behavior that cultivates a culture of inclusion and communication equality (community) in an inclusive school setting. Meanwhile, teachers symbolically expand interactive spaces and facilitate inclusion. In hearing-Impaired education, social and cultural meanings, identity, and relationships develop through communicative methods that are predominantly nonverbal, such as BISINDO. Supported by cognitive engagement, self-reflection, and an inclusive environment, teachers can bring inclusive attributes into the learning space, ultimately promoting inclusive education.

We investigate the effects of word characteristics on episodic recognition memory using analyses that avoid Clark’s (1973) “language-as-a-fixed-effect” fallacy. Our results demonstrate the importance of modeling word variability and show that episodic memory for words is strongly affected by item noise ( Criss & Shiffrin, 2004), as measured by the orthographic similarity between experimental items. We found that the word frequency effect was not related to the item noise effects, whereas the effect of neighborhood density, which measures the similarity of a word to all other words in the lexicon, was greatly attenuated when item noise was controlled. Our results are also consistent with a likelihood based recognition decision mechanism that produces a mirror effect by taking into account item and subject characteristics.

Item-specific and relational encoding effects in children's recall and recognition memory for words

This study aimed to develop and validate an instrument to measure students' cognitive engagement in teaching-learning environments. An exploratory correlational method was employed to develop the scale. 446 university pre‐degree students learning English as a foreign language participated in the study. A pilot study was conducted with 117 students to explore the item and factor structure of the scale, resulting in the removal of eight items from the scale. A subsequent study with 329 students was conducted to confirm the scale's item and factor structure. Results showed that the scale demonstrated content validity, with a content validity index of .94. The scale consisted of nine items and two factors, identified as cognitive attention and cognitive effort. Convergent validity was established, as evidenced by composite reliability values of .83 and .84 for each factor, with average variance extracted of .55 and .51, respectively. Corrected item-total correlation values ranged from .54 to .71, and inter-item correlation exceeded .30. Reliability analysis revealed high internal consistency, with each factor demonstrating reliability of .83 and .85, resulting in an overall scale reliability of .89. In conclusion, the findings indicate that the developed PSCP Cognitive Engagement Scale is a valid and reliable scale for measuring cognitive engagement in learning environments.

The objective of the current research is to analyze the effect of psychological need satisfaction on intrinsic motivation and cognitive engagement in terms of higher education and through the theoretical idea of Self-Determination Theory (SDT). The study will seek to address a gap in knowledge that is a critical one as far as the determination of how the perceptions of students towards autonomy, competence, and relatedness can not only lead to their motivation but also that of cognitive investment with regard to learning to which they invest. The research will be conducted in mixed format, with quantitative data analysis method of the structured surveys completed by 200 university students, and quantitative data analysis of 30 semi-structured interviews (so that no more than one hour is spent on each interview). It is thanks to this two-fold strategy that both measurable trends and lived lives can be approached as a whole. The results indicate mediating impact of the intrinsic motivation between the fulfillment of the psychological needs, and cognitive engagement, and therefore the significance of internalized drive in development of meaningful learning behaviors. The best indicator of engagement was competence, as compared to other two psychological needs that imply that students who perceive themselves as capable and skilled will be more likely to put more cognitive efforts in their study work. In addition to that, the findings indicate the importance of the autonomy-supportive environment and the favorable relations with the peers and instructors which, when united, contribute to the promotion of the motivation and persistence of the students in the academic life. Theoretically, the current study is an extension of SDT since it proposes the elements of Expectancy-Value theory and the Achievement Goal Theory since it offers a more holistic motivational concept. It also takes to account cultural dimension which identifies the perception of autonomy and relatedness of students therefore providing a more comprehensive and context sensitive interpretation of the motivational mystery in learning institutions.

Abstract. Geographic information science (GIScience) education has undergone enormous changes over the past years. One major factor influencing this change is the role of the geospatial web in GIScience. In addition to the use of the web for enabling and enhancing GIScience education, it is also used as the infrastructure for communicating and collaborating among geospatial data and users. The web becomes both the means and the content for a geospatial education program. However, the web does not replace the traditional face-to-face environment, but rather is a means to enhance it, expand it and enable an authentic and real world learning environment. This paper outlines the use of the web in both the delivery and content of the GIScience program at Curtin University. The teaching of the geospatial web, web and cloud based mapping, and geospatial web services are key components of the program, and the use of the web and online learning are important to deliver this program. Some examples of authentic and real world learning environments are provided including joint learning activities with partner universities.

The ability to attain knowledge for implementation within real-world environments is a shift in understanding within many instructional environments. Shifting from competency-based understandings wherein a knowledge base is attained as well as implemented towards a capability-based understanding that emphasizes the conceptual framework of information shift towards higher order knowledge creation within novel situations and environments is essential. Lifelong learning within nuanced understandings of new situations and new experiences is essential. Normally, these novel situations and experiences occur within a real-world community environment wherein the learner is critically analyzing new information and opinions from innumerable engaged people within the community. This style of learning is vital to understand within a competency-based learning environment, as well. Therefore, real-world instructional learning embeds the supporting community engagement at distinctly appropriate and impactful points throughout the instructional process, resulting in outstanding conceptual frameworks with the continuous understanding around cognitive engagement.

Evaluating adaptive and attentional accounts of sensorimotor effects in word recognition memory