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Abstract Background Serious games are risk-free environments training various medical competencies, such as clinical reasoning, without endangering patients’ safety. Furthermore, serious games provide a context for training situations with unpredictable outcomes. Training these competencies is particularly important for healthcare professionals in emergency medicine. Methods Based on these considerations, we designed, implemented, and evaluated a serious game in form of an emergency department, containing the features of a virtual patient generator, a chatbot for medical history taking with self-formulated questions, artificially generated faces based on an artificial intelligence algorithm, and feedback for students. The development process was based on an already existing framework resulting in an iterative procedure between development and evaluation. The serious game was evaluated using the System Usability Scale and the User Experience Questionnaire. Results The System Usability Scale provided a substantial result for the usability. In terms of the user experience, four scales yielded positive results, whereas two scales yielded neutral results. Conclusion The evaluation of both usability and user experience yielded overall positive results, while simultaneously identifying potential areas for improvement. Further studies will address the implementation of additional game design elements, and testing student learning outcome.

Abstract Background Artificial intelligence (AI) is becoming increasingly important in healthcare. It is therefore crucial that today’s medical students have certain basic AI skills that enable them to use AI applications successfully. These basic skills are often referred to as “AI literacy”. Previous research projects that aimed to investigate medical students’ AI literacy and attitudes towards AI have not used reliable and validated assessment instruments. Methods We used two validated self-assessment scales to measure AI literacy (31 Likert-type items) and attitudes towards AI (5 Likert-type items) at two German medical schools. The scales were distributed to the medical students through an online questionnaire. The final sample consisted of a total of 377 medical students. We conducted a confirmatory factor analysis and calculated the internal consistency of the scales to check whether the scales were sufficiently reliable to be used in our sample. In addition, we calculated t-tests to determine group differences and Pearson’s and Kendall’s correlation coefficients to examine associations between individual variables. Results The model fit and internal consistency of the scales were satisfactory. Within the concept of AI literacy, we found that medical students at both medical schools rated their technical understanding of AI significantly lower (M MS1 = 2.85 and M MS2 = 2.50) than their ability to critically appraise (M MS1 = 4.99 and M MS2 = 4.83) or practically use AI (M MS1 = 4.52 and M MS2 = 4.32), which reveals a discrepancy of skills. In addition, female medical students rated their overall AI literacy significantly lower than male medical students, t(217.96) = -3.65, p

Motivated by a holistic understanding of AI literacy, this work presents an interdisciplinary effort to make AI literacy measurable in a comprehensive way, considering generic and domain-specific AI literacy as well as AI ethics. While many AI literacy assessment tools have been developed in the last 2-3 years, mostly in the form of self-assessment scales and less frequently as knowledge-based assessments, previous approaches only accounted for one specific area of a comprehensive understanding of AI competence, namely cognitive aspects within generic AI literacy. Considering the demand for AI literacy development for different professional domains and reflecting on the concept of competence in a way that goes beyond mere cognitive aspects of conceptual knowledge, there is an urgent need for assessment methods that capture domain-specific AI literacy on each of the three competence dimensions of cognition, behavior, and attitude. In addition, competencies for AI ethics are becoming more apparent, which further calls for a comprehensive assessment of AI literacy for this very matter. This conceptual paper aims to provide a foundation upon which future AI literacy assessment instruments can be built and provides insights into what a framework for item development might look like that addresses both generic and domain-specific aspects of AI literacy as well as AI ethics literacy, and measures more than just knowledge-related aspects based on a holistic approach.

Artificial Intelligence competencies will become increasingly important in the near future. Therefore, it is essential that the AI literacy of individuals can be assessed in a valid and reliable way. This study presents the development of the “Scale for the assessment of non-experts' AI literacy” (SNAIL). An existing AI literacy item set was distributed as an online questionnaire to a heterogeneous group of non-experts (i.e., individuals without a formal AI or computer science education). Based on the data collected, an exploratory factor analysis was conducted to investigate the underlying latent factor structure. The results indicated that a three-factor model had the best model fit. The individual factors reflected AI competencies in the areas of “Technical Understanding”, “Critical Appraisal”, and “Practical Application”. In addition, eight items from the original questionnaire were deleted based on high intercorrelations and low communalities to reduce the length of the questionnaire. The final SNAIL-questionnaire consists of 31 items that can be used to assess the AI literacy of individual non-experts or specific groups and is also designed to enable the evaluation of AI literacy courses’ teaching effectiveness.

Artificial intelligence literacy is a concept that has been the focus of exhaustive research recently. However, there are very few psychometrically sound and thoroughly evaluated instruments that attempt to assess AI literacy in a valid way. Therefore, this study presents an item set to assess the AI literacy of non-experts. In the context of a Delphi expert study, 53 subject matter experts participated in three iterative questionnaire rounds to generate potential AI literacy items and assess their content validity. In addition, the experts made suggestions on how the items’ wording accuracy could be improved and evaluated the wording suggestions of the other experts. Of 47 potential items, 38 were judged relevant for inclusion in a final AI literacy questionnaire. The result is one of the first freely available AI literacy item sets and represents an important first step in assessing AI literacy and its subconstructs. Finally, the development of the items through the execution of an iterative Delphi study and the strong focus on content validity contribute to the advancement of AI literacy theory.

The use of artificial intelligence (AI) is becoming increasingly important in various domains, making education about AI a necessity. The interdisciplinary nature of AI and the relevance of AI in various fields require that university instructors and course developers integrate AI topics into the classroom and create so-called domain-specific AI courses. In this paper, we introduce the “AI Course Design Planning Framework” as a course planning framework to structure the development of domain-specific AI courses at the university level. The tool evolves non-specific course planning frameworks to address the context of domain-specific AI education. Following a design-based research approach, we evaluated a first prototype of the tool with instructors in the field of AI education who are developing domain-specific courses in this area. The results of our evaluation indicate that the tool allows instructors to create domain-specific AI courses in an efficient and comprehensible way. In general, instructors rated the tool as useful and user-friendly and made recommendations to improve its usability. Future research will focus on testing the application of the tool for domain-specific AI course developments in different domain contexts and examine the influence of using the tool on AI course quality and learning outcomes.

A growing number of courses seek to increase the basic artificial-intelligence skills (“AI literacy”) of their participants. At this time, there is no valid and reliable measurement tool that can be used to assess AI-learning gains. However, the existence of such a tool would be important to enable quality assurance and comparability. In this study, a validated AI-literacy-assessment instrument, the “scale for the assessment of non-experts’ AI literacy” (SNAIL) was adapted and used to evaluate an undergraduate AI course. We investigated whether the scale can be used to reliably evaluate AI courses and whether mediator variables, such as attitudes toward AI or participation in other AI courses, had an influence on learning gains. In addition to the traditional mean comparisons (i.e., t-tests), the comparative self-assessment (CSA) gain was calculated, which allowed for a more meaningful assessment of the increase in AI literacy. We found preliminary evidence that the adapted SNAIL questionnaire enables a valid evaluation of AI-learning gains. In particular, distinctions among different subconstructs and the differentiation constructs, such as attitudes toward AI, seem to be possible with the help of the SNAIL questionnaire.

Morphological left-right brain asymmetries are universal phenomena in animals. These features have been studied for decades, but the functional relevance is often unclear. Studies from the zebrafish dorsal diencephalon on the genetics underlying the establishment and function of brain asymmetries have uncovered genes associated with the development of functional brain asymmetries. To gain further insights, comparative studies help to investigate the emergence of asymmetries and underlying genetics in connection to functional adaptation. Evolutionarily distant isogenic medaka inbred lines, that show divergence of complex traits such as morphology, physiology and behavior, are a valuable resource to investigate intra-species variations in a given trait of interest. For a detailed study of asymmetry in the medaka diencephalon we generated molecular probes of ten medaka genes that are expressed asymmetrically in the zebrafish habenulae and pineal complex. We find expression of eight genes in the corresponding brain areas of medaka with differences in the extent of left-right asymmetry compared to zebrafish. Our marker gene analysis of the diverged medaka inbred strains revealed marked inter-strain size differences of the respective expression domains in the parapineal and the habenulae, which we hypothesize may result from strain-specific gene loss. Thus, our analysis reveals both inter-species differences but also intra-species plasticity of gene expression in the teleost dorsal diencephalon. These findings are a starting point showing the potential to identify the genetics underlying the emergence and modulations of asymmetries. They are also the prerequisite to examine whether variance in habenular gene expression may cause variation of behavioral traits.

Serious games, as a learning resource, enhance their game character by embedding game design elements that are typically used in entertainment games. Serious games in its entirety have already proven their teaching effectiveness in different educational contexts including medical education. The embedded game design elements play an essential role for a game's effectiveness and thus they should be selected based on evidence-based theories. For game design elements embedded in serious games used for the education of medical and healthcare professions, an overview of theories for the selection lacks. Additionally, it is still unclear whether and how single game design elements affect the learning effectiveness. Therefore, the main aim of this systematic review is threefold. Firstly, light will be shed on the single game design elements used in serious games in this area. Second, the game design elements' underlying theories will be worked out, and third, the game design elements' effectiveness on student learning outcome will be assessed. Two literature searches were conducted in November 2021 and May 2022 in six literature databases with keywords covering the fields of educational game design, serious game, and medical education. Out of 1006 initial records, 91 were included after applying predefined exclusion criteria. Data analysis revealed that the three most common game design elements were points, storyline, and feedback. Only four underlying theories were mentioned, and no study evaluated specific game design elements. Since game design elements should be based on theories to ensure meaningful evaluations, the conceptual GATE framework is introduced, which facilitates the selection of evidence-based game design elements for serious games.

Since artificial intelligence (AI) is finding its way into more and more areas of everyday life, improving the AI skills of non-experts is important and will become even more relevant in the future. While it is necessary that children learn about the possibilities of AI at an early age, adults in higher education and beyond should also have at least a basic understanding of AI (i.e., AI literacy) to be able to interact effectively with the technology. To evaluate the current state of the literature on AI literacy in higher and adult education, a scoping literature review was conducted with the objective of identifying thematic foci and recent research trends. Ten research databases were searched and out of 902 initial records, 30 studies were identified using predefined eligibility criteria, whereof the content was evaluated in the review. The results indicated that research in this area is still in its infancy and needs refinement in terms of how to define AI literacy in adult education as well as what content should be taught to non-experts. Lastly, several recommendations for research and practice are derived from the results.

The prevalence of patients suffering from mental disorders is substantially increasing in recent years and represents a major burden to society. The underlying causes and neuronal circuits affected are complex and difficult to unravel. Frequent disorders such as depression, schizophrenia, autism, and bipolar disorder share links to the habenular neural circuit. This conserved neurotransmitter system relays cognitive information between different brain areas steering behaviors ranging from fear and anxiety to reward, sleep, and social behaviors. Advances in the field using the zebrafish model organism have uncovered major genetic mechanisms underlying the formation of the habenular neural circuit. Some of the identified genes involved in regulating Wnt/beta-catenin signaling have previously been suggested as risk genes of human mental disorders. Hence, these studies on habenular genetics contribute to a better understanding of brain diseases. We are here summarizing how the gained knowledge on the mechanisms underlying habenular neural circuit development can be used to introduce defined manipulations into the system to study the functional behavioral consequences. We further give an overview of existing behavior assays to address phenotypes related to mental disorders and critically discuss the power but also the limits of the zebrafish model for identifying suitable targets to develop therapies.

Dihydropteridine reductase (QDPR) catalyzes the recycling of tetrahydrobiopterin (BH4), a cofactor in dopamine, serotonin, and phenylalanine metabolism. QDPR-deficient patients develop neurological symptoms including hypokinesia, truncal hypotonia, intellectual disability and seizures. The underlying pathomechanisms are poorly understood. We established a zebrafish model for QDPR deficiency and analyzed the expression as well as function of all zebrafish QDPR homologues during embryonic development. The homologues qdpra is essential for pigmentation and phenylalanine metabolism. Qdprb1 is expressed in the proliferative zones of the optic tectum and eye. Knockdown of qdprb1 leads to up-regulation of pro-proliferative genes and increased number of phospho-histone3 positive mitotic cells. Expression of neuronal and astroglial marker genes is concomitantly decreased. Qdprb1 hypomorphic embryos develop microcephaly and reduced eye size indicating a role for qdprb1 in the transition from cell proliferation to differentiation. Glutamine accumulation biochemically accompanies the developmental changes. Our findings provide novel insights into the neuropathogenesis of QDPR deficiency.

The coordinated interplay between extrinsic activating and repressing cell signaling molecules is pivotal for embryonic development and subsequent tissue homeostasis. This is well exemplified by studies on the evolutionarily conserved Wnt signaling pathways. Tight temporal and spatial regulation of Wnt signaling activity is required throughout lifetime, from maternal stages before gastrulation until and throughout adulthood. Outside cells, the action of numerous Wnt ligands is counteracted and fine-tuned by only a handful of well characterized secreted inhibitors, such as for instance Dickkopf, secreted Frizzled Related Proteins and Cerberus. Here, we give an overview of our current understanding of another secreted Wnt signaling antagonist, the Wnt inhibitory factor Wif1. Wif1 can directly interact with various Wnt ligands and inhibits their binding to membrane bound receptors. Epigenetic promoter methylation of Wif1, leading to silencing of its transcription and concomitant up-regulation of Wnt signaling, is a common feature during cancer progression. Furthermore, an increasing number of reports describe Wif1 involvement in regulating processes during embryonic development, which so far has not received as much attention. We will summarize our knowledge on Wif1 function and its mode of action with a particular focus on the zebrafish (Danio rerio). In addition, we highlight the potential of Wif1 research to understand and possibly influence mechanisms underlying eye diseases and regeneration.

Hyperammonemia is the common biochemical hallmark of urea cycle disorders, activating neurotoxic pathways. If untreated, affected individuals have a high risk of irreversible brain damage and mortality. Here we show that acute hyperammonemia strongly enhances transamination-dependent formation of osmolytic glutamine and excitatory glutamate, thereby inducing neurotoxicity and death in ammoniotelic zebrafish larvae via synergistically acting overactivation of NMDA receptors and bioenergetic impairment induced by depletion of 2-oxoglutarate. Intriguingly, specific and irreversible inhibition of ornithine aminotransferase (OAT) by 5-fluoromethylornithine rescues zebrafish from lethal concentrations of ammonium acetate and corrects hyperammonemia-induced biochemical alterations. Thus, OAT inhibition is a promising and effective therapeutic approach for preventing neurotoxicity and mortality in acute hyperammonemia.

Wnt/β-catenin signaling plays an important role in embryonic development and adult tissue homeostasis. When Wnt ligands bind to the receptor complex, LRP5/6 coreceptors are activated by phosphorylation and concomitantly endocytosed. In vertebrates, Wnt ligands induce caveolin-dependent endocytosis of LRP6 to relay signal downstream, whereas antagonists such as Dickkopf promote clathrin-dependent endocytosis, leading to inhibition. However, little is known about how LRP6 is directed to different internalization mechanisms, and how caveolin-dependent endocytosis is mediated. In an RNAi screen, we identified the Rab GTPase RAB8B as being required for Wnt/β-catenin signaling. RAB8B depletion reduces LRP6 activity, β-catenin accumulation, and induction of Wnt target genes, whereas RAB8B overexpression promotes LRP6 activity and internalization and rescues inhibition of caveolar endocytosis. In Xenopus laevis and Danio rerio, RAB8B morphants show lower Wnt activity during embryonic development. Our results implicate RAB8B as an essential evolutionary conserved component of Wnt/β-catenin signaling through regulation of LRP6 activity and endocytosis.

Monitoring cycling behaviours of stem and somatic cells in the living animal is a powerful tool to better understand tissue development and homeostasis. The tg(anillin:anillin-eGFP) transgenic line carries the full-length zebrafish F-actin binding protein Anillin fused to eGFP from a bacterial artificial chromosome (BAC) containing Anillin cis-regulatory sequences. Here we report the suitability of the Anillin-eGFP reporter as a direct indicator of cycling cells in the late embryonic and post-embryonic retina. We show that combining the anillin:anillin-eGFP with other transgenes such as ptf1a:dsRed and atoh7:gap-RFP allows obtaining spatial and temporal resolution of the mitotic potentials of specific retinal cell populations. This is exemplified by the analysis of the origin of the previously reported apically and non-apically dividing late committed precursors of the photoreceptor and horizontal cell layers.

The analysis of genes in evolutionarily distant but morphologically similar species is of major importance to unravel the changes in genomes over millions of years, which led to gene silencing and functional diversification. We report the analysis of Wnt8a gene expression in the medakafish and provide a detailed comparison to other vertebrates. In all teleosts analyzed there are two paralogous Wnt8a copies. These show largely overlapping expression in the early developing zebrafish embryo, an evolutionarily distant relative of medaka. In contrast to zebrafish, we find that both maternal and zygotic expression of particularly one Wnt8a paralog has diverged in medaka. While Wnt8a1 expression is mostly conserved at early embryonic stages, the expression of Wnt8a2 differs markedly. In addition, both genes are distinctly expressed during organogenesis unlike the zebrafish homologs, which may hint at the emergence of functional diversification of Wnt8a ligands during evolution.

Serious games, as a learning resource, enhance their game character by embedding game design elements that are typically used in entertainment games. Serious games in its entirety have already proven their teaching effectiveness in different educational contexts including medical education. The embedded game design elements play an essential role for a game's effectiveness and thus they should be selected based on evidence-based theories. For game design elements embedded in serious games used for the education of medical and healthcare professions, an overview of theories for the selection lacks. Additionally, it is still unclear whether and how single game design elements affect the learning effectiveness. Therefore, the main aim of this systematic review is threefold. Firstly, light will be shed on the single game design elements used in serious games in this area. Second, the game design elements' underlying theories will be worked out, and third, the game design elements' effectiveness on student learning outcome will be assessed. Two literature searches were conducted in November 2021 and May 2022 in six literature databases with keywords covering the fields of educational game design, serious game, and medical education. Out of 1006 initial records, 91 were included after applying predefined exclusion criteria. Data analysis revealed that the three most common game design elements were points, storyline, and feedback. Only four underlying theories were mentioned, and no study evaluated specific game design elements. Since game design elements should be based on theories to ensure meaningful evaluations, the conceptual GATE framework is introduced, which facilitates the selection of evidence-based game design elements for serious games. [ABSTRACT FROM AUTHOR]

Background: Serious games are risk-free environments training various medical competencies, such as clinical reasoning, without endangering patients' safety. Furthermore, serious games provide a context for training situations with unpredictable outcomes. Training these competencies is particularly important for healthcare professionals in emergency medicine. Methods: Based on these considerations, we designed, implemented, and evaluated a serious game in form of an emergency department, containing the features of a virtual patient generator, a chatbot for medical history taking with self-formulated questions, artificially generated faces based on an artificial intelligence algorithm, and feedback for students. The development process was based on an already existing framework resulting in an iterative procedure between development and evaluation. The serious game was evaluated using the System Usability Scale and the User Experience Questionnaire. Results: The System Usability Scale provided a substantial result for the usability. In terms of the user experience, four scales yielded positive results, whereas two scales yielded neutral results. Conclusion: The evaluation of both usability and user experience yielded overall positive results, while simultaneously identifying potential areas for improvement. Further studies will address the implementation of additional game design elements, and testing student learning outcome. [ABSTRACT FROM AUTHOR]