Final Score Research Articles

Application of BPNN’s intelligent ETQ model in network English teaching

Teaching evaluation is a key initiative to improve the quality of education and teaching. The research significance of this study is rooted in addressing the limitations of the traditional evaluation of teaching quality (ETQ) model, which often relies on a single evaluation index, exhibits a one-sided perspective, and suffers from pronounced subjectivity. In this context, this paper delves into the application of the backpropagation neural network (BPNN) to enhance and refine the ETQ model. The intelligent ETQ model was constructed and utilized in network English teaching to enhance the effect and quality of network English teaching. By analyzing the characteristics and needs of network English teaching, the advantages of BPNN in the ETQ were explored. The intelligent evaluation model was constructed, and its application effect in network English teaching was studied and evaluated. The total number of students satisfied with the BPNN based network English ETQ model was 151, with a total satisfaction rate of 75.5%. The ETQ model on the basis of BPNN was applied to network English teaching, which helped the average final score of Class 2 improve by 5.44 points compared to the division exam. The ETQ model based on BPNN was applied to network English teaching, which can improve the rationality of teaching evaluation and help improve students’ school English proficiency.

Safety, Efficacy and Outcome of Rotational Thrombectomy assisted Endovascular Revascularisation of the Superior Mesenteric Artery in Acute Thromboembolic Mesenteric Ischaemia.

To evaluate the efficacy and safety of percutaneous rotational thrombectomy-assisted endovascular revascularization of acute thromboembolic superior mesenteric artery occlusions in acute mesenteric ischemia. Fifteen cases of percutaneous rotational thrombectomy- assisted (Rotarex S, BD, USA) revascularization were retrospectively analyzed. The etiology was embolic in 40 % of cases and thrombotic in 60 %. A "Thrombectomy in Visceral Ischemia" (TIVI) 5-point score determined vessel patency at presentation, after percutaneous rotational thrombectomy, and after adjunctive technologies. TIVI 3 indicated nearly complete revascularization (minimal residual side branch thrombus). TIVI 4 indicated complete revascularization. Technical success was defined as successful device application and a final TIVI score of 3/4 after adjunctive technologies. Safety and outcome were also analyzed. Device application via femoral access was feasible in 100 % of cases and improved flow in 86.7 % of cases (1 × TIVI 0→1, 11 × TIVI 0→2, 1 × TIVI 1→2). There was no change in 13.3 % of cases (2 × TIVI 2→2). Additional devices resulted in further flow improvement in 93.3 % of cases (8 × TIVI 3, 6 × TIVI 4). One recanalization failed (TIVI 2→2→2). After adjunctive technologies (10 × manual aspiration, 11 × angioplasty, 9 × stenting), the technical success rate was 93.3 %. The mean procedure time was 40.5(± 14) minutes for embolism and 72.1(± 20) minutes for thrombosis. There was one device-related major complication (catheter tip fracture) resulting in a device-related safety rate of 93.3 %. The overall major complication rate was 20 %. Surgical exploration (13 ×), bowel resection (9 ×) and Fogarty embolectomy/bypass (3 ×) were also performed. The 30-day mortality rate was 40 %. Percutaneous rotational thrombectomy is an effective adjunct for rapid endovascular recanalization of acute thromboembolic superior mesenteric artery occlusions with an acceptable rate of major procedural complications. · Percutaneous rotational thrombectomy-assisted superior mesenteric artery revascularization in acute occlusive mesenteric ischemia is feasible and effective.. · Percutaneous rotational thrombectomy facilitates rapid flow restoration in native and stented superior mesenteric artery segments.. · Brachial access should be considered in the case of steep take-off angles of the superior mesenteric artery..

The Impact of Blocked Practice versus Mixed Practice and the Strategy of Overlearning on Student Performance in Calculus

ABSTRACT In most mathematics textbooks, each lesson is followed by a set of homework problems in one of two ways – blocked practice and mixed practice. Additionally, most mathematics textbooks rely on a common learning strategy called overlearning, that is, mastering a skill and continuing to practice this same skill. This study investigated the effects of blocked practice versus mixed practice and the overlearning strategy on student performance in a university-level Calculus I classroom using an online homework system. Data collection took place throughout the semester and included student scores on homework and exams. An ANCOVA was used to analyze the data and the results indicated that there were no statistically significant differences on final exam scores between the participants in the blocked and mixed practice groups. Additionally, the 50% increase in the number of homework problems per set (i.e. overlearning) did not show statistically significant differences in student performance as measured on final exam scores.

A trustworthy data collection approach from sensor nodes using trust score of mobile vehicles for smart city

AbstractIn smart cities, a substantial amount of data is collected for analytics and a better life for the citizens. The schemes based on data collection through mobile vehicles (MV) and further verification of that data through unmanned aerial vehicles (UAV) are popular. Many trust‐based schemes of the MV have been proposed recently. However, these schemes suffered from recognition accuracy, judgment trust, and collusion attack problems. In this paper, we propose a Gompetz function‐based trust evaluation scheme. In this scheme, the direct trust of the MV is computed by comparing the data provided by the MV and the same reported by the UAV. Since the UAV can collect only limited data, indirect trust of the vehicle is computed by comparing the data reported by the MV and the same reported by the MV having the highest trust. We also applied the variable trust, which considers the recent Trust of the MVs. Then, combining all these trusts with significant weight, the final trust score of the MV is computed. After experimenting, our proposed scheme is more credible and removes the shortcomings of the existing methods by providing better recognition, accuracy, judgment, and trust.

MACHINE LEARNING (AI) FOR IDENTIFYING SMART CITIES

Abstract. Cities worldwide are attempting to be claimed as smart, but truly classifying as such remains a great challenge. This paper aims to use artificial intelligence AI to classify the smart city's performance as well as the factors linked to it. This is based on the perceptions of residents on issues related to structures and technology applications available in their cities. To achieve this goal, the study included 200 cities worldwide. For 147 cities we captured the perceptions of 120 residents in each city, by answering a survey of 39 questions evolving around two main Pillars: ‘Structures’ that refers to the existing infrastructure of the city and the ‘Technology’ pillar that describes the technological provisions and services available to the inhabitants. And each one is evaluated under five key areas: health and safety, mobility, activities, opportunities, and governance. The final score of the other 53 cities, was measured by using the data openly available on the internet. And this by means of different algorithms of machine learning such as Random Forest RF, Artificial Neural Network ANN, Support Vector Machine (SVM), and Gradient Boost (XGB). These algorithms have been compared and evaluated in order to select the best one. The tests showed that Random Forest RF alongside with Artificial Neural Network ANN, with the highest level of accuracy, are the best trained model. This study will enable other researches to use machine learning in the identification process of smart cities.

Conformity of ChatGPT recommendations with the AUA/SUFU guideline on postprostatectomy urinary incontinence.

Artificial intelligence (AI) shows immense potential in medicine and Chat generative pretrained transformer (ChatGPT) has been used for different purposes in the field. However, it may not match the complexity and nuance of certain medical scenarios. This study evaluates the accuracy of ChatGPT 3.5 and 4 in providing recommendations regarding the management of postprostatectomy urinary incontinence (PPUI), considering The Incontinence After Prostate Treatment: AUA/SUFU Guideline as the best practice benchmark. A set of questions based on the AUA/SUFU Guideline was prepared. Queries included 10 conceptual questions and 10 case-based questions. All questions were open and entered into the ChatGPT with a recommendation to limit the answer to 200 words, for greater objectivity. Responses were graded as correct (1 point); partially correct (0.5 point), or incorrect (0 point). Performances of versions 3.5 and 4 of ChatGPT were analyzed overall and separately for the conceptual and the case-based questions. ChatGPT 3.5 scored 11.5 out of 20 points (57.5% accuracy), while ChatGPT 4 scored 18 (90.0%; p = 0.031). In the conceptual questions, ChatGPT 3.5 provided accurate answers to six questions along with one partially correct response and three incorrect answers, with a final score of 6.5. In contrast, ChatGPT 4 provided correct answers to eight questions and partially correct answers to two questions, scoring 9.0. In the case-based questions, ChatGPT 3.5 scored 5.0, while ChatGPT 4 scored 9.0. The domains where ChatGPT performed worst were evaluation, treatment options, surgical complications, and special situations. ChatGPT 4 demonstrated superior performance compared to ChatGPT 3.5 in providing recommendations for the management of PPUI, using the AUA/SUFU Guideline as a benchmark. Continuous monitoring is essential for evaluating the development and precision of AI-generated medical information.

Information Security Risk Measurement Using Information Security Index (KAMI) at Information Technology And Database Center (PTIPD)

UIN Sunan Gunung Djati Bandung, as a rapidly growing higher education institution, faces great challenges in ensuring information security. This research aims to improve information security at UIN Sunan Gunung Djati Bandung by applying the Information Security Index (KAMI). This method is used to analyze information security risks with the aim of identifying potential threats, vulnerabilities, and possible impacts. The results of the analysis revealed that there are security measures already in place, but also highlighted areas that require further attention. By achieving a final score of 415, signifying category II (Basic Framework Fulfillment), this research made a significant contribution to the understanding of information security in higher education. Through the application of WE, this research not only provides a comprehensive overview of the status of information security at UIN Sunan Gunung Djati Bandung, but also opens up opportunities to identify and address potential threats more effectively. Thus, the results of this study have important implications in improving information security and protection in higher education institutions, and can be a valuable guide for similar institutions in their efforts to mitigate information security risks.

Meta Analysis Study: Theory of Planned Behavior in Whistleblowing Intention

Indonesia's Corruption Perception Index in 2022 had decreased significantly with a final score of 34 points and ranked Indonesia 110 out of 180 countries. It shows that corruption practices in Indonesia are high and the strategy for combating fraud is not effective. In practice, the fraud management strategies focus on improving internal control systems than preventive strategies such as whistleblowing system. This is due to the low intention of individuals to disclose fraud. Whistleblowers will encounter risks in organization, such as different prespective and norms in organization and the confidentiality and safety risk. Therefore, individuals need to carefully consider before deciding to become whistleblowers This study is aimed to examine individual factors that influence whistleblowing intention by the theory of planned behavior using meta-analysis technique, a quantitative method to measure the strength of the relationship of variables from previous research. Fourteen of the 53 selected studies were analyzed according to the eligibility criteria, the results is the highest correlation is the attitude toward behavior, then the subjective norm , and the lowest is the perceived behavioral control. It indicates that organization needs to stimulate an increase individual’s intention to disclose fraud by whistleblowing system as prevention strategy to combat fraud.

Dental students in an orthodontic course flipped classroom: A semi-experimental study on knowledge, practice, attitude, and satisfaction.

The purpose of this study was to determine the students' attitudes before and after the flipped classroom, and the effectiveness of this method to promote the students' lateral cephalograms tracing abilities, students' satisfaction and their final exam scores. This is a single-group quasi-experimental research conducted on dental students of Shiraz University of Medical Sciences (SUMS), Iran in 2019. The intervention was carried out in a blended learning approach with the flipped classroom model. Thirty-five fourth-year dental students participated in a flipped classroom held during a semester for the lateral cephalograms tracing course. The students were provided with the educational materials before the class time through multimedia learning tools and the class time was devoted to discussions. The students were asked to fill out four questionnaires (pretest/posttest attitudes, pretest/posttest self-assessments of theoretical knowledge and practical skills in cephalograms, posttest of satisfaction from quality of the course, and posttest of students' views about effectiveness of blended learning tools) and final exam scores of students. Students' attitudes toward e-Learning were improved after the flipped classroom and the quality of this method was acceptable to the students (p < .001). Their self-assessment of theoretical knowledge and practical skills were promoted (p < .001). While all blended learning tools averaged more than the cut-off-point, short lecture (5.11 ± 0.98) and live feedback (4.98 ± 1.07) were considered to be the most efficient interactive tools. It seems that the flipped classroom has a positive effect on increasing students' knowledge, attitude, and satisfaction. In general, this method of learning seems to be favored by dental students. The findings showed that blended learning had a positive effect on increasing knowledge, performance, and satisfaction among dental students. Therefore, blended learning as a reliable method might be used in training dental students.

Early Weight-bearing Following Surgical Treatment of Ankle Fractures Without Trans-syndesmotic Fixation Is Safe and Improves Short-term Outcomes.

The objective of this study was to ascertain outcome differences after fixation of unstable rotational ankle fractures allowed to weight-bear 2 weeks postoperatively compared with 6 weeks. Prospective case-control study. Academic medical center; Level 1 trauma center. Patients with unstable ankle fractures (OTA/AO:44A-C) undergoing open reduction internal fixation (ORIF) were enrolled. Patients requiring trans-syndesmotic fixation were excluded. Two surgeons allowed weight-bearing at 2 weeks postoperatively (early weight-bearing [EWB] cohort). Two other surgeons instructed standard non-weight-bearing until 6 weeks postoperatively (non-weight-bearing cohort). The main outcome measures included the Olerud-Molander questionnaire, the SF-36 questionnaire, and visual analog scale at 6 weeks, 3 months, 6 months, and 12 months postoperatively and complications, return to work, range of ankle motion, and reoperations at 12 months were compared between the 2 cohorts. One hundred seven patients were included. The 2 cohorts did not differ in demographics or preinjury scores ( P > 0.05). Six weeks postoperatively, EWB patients had improved functional outcomes as measured by the Olerud-Molander and SF-36 questionnaires. Early weight-bearing patients also had better visual analog scale scores (standardized mean difference -0.98, 95% confidence interval [CI] -1.27 to -0.70, P < 0.05) and a greater proportion returning to full capacity work at 6 weeks (odds ratio = 3.42, 95% CI, 1.08-13.07, P < 0.05). One year postoperatively, EWB patients had improved pain measured by SF-36 (standardized mean difference 6.25, 95% CI, 5.59-6.92, P < 0.01) and visual analog scale scores (standardized mean difference -0.05, 95% CI, -0.32 to 0.23, P < 0.01). There were no differences in complications or reoperation at 12 months ( P > 0.05). EWB patients had improved early function, final pain scores, and earlier return to work, without an increased complication rate compared with those kept non-weight-bearing for 6 weeks. Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.

Development of E-Module Based on Mathematical Literacy Skill in Statistical Materials

This research aims to produce an E-Module with math literacy-based questions that are valid and practical for 10th-grade statistics in SMA Negeri 3 Padang. The type of research conducted is development research using the ADDIE development model. Data analysis techniques include interview analysis, E-Module validation analysis, and E-Module practicality analysis. The results of the research show that mathematics learning using the E-Module, which facilitates mathematical literacy questions, is both valid and practical. Based on the data analysis, it was found that the developed E-Module had a validity score of 92.31%, categorized as highly valid. The final practicality score for teachers was 85%, categorized as highly practical, and the final practicality score for students was 88.26%, also categorized as highly practical.

Leveraging Biotic Interaction Knowledge Graph and Network Analysis to Uncover Insect Vectors of Plant Virus

Background: Insect vectors spread 80% of plant viruses, causing major agricultural production losses. Direct insect vector identification is difficult due to a wide range of hosts, limited detection methods, and high PCR costs and expertise. Currently, a biodiversity database named Global Biotic Interaction (GloBI) provides an opportunity to identify virus vectors using its data. Objective: This study aims to build an insect vector search engine that can construct an virus-insect-plant interaction knowledge graph, identify insect vectors using network analysis, and extend knowledge about identified insect vectors. Methods: We leverage GloBI data to construct a graph that shows the complex relationships between insects, viruses, and plants. We identify insect vectors using interaction analysis and taxonomy analysis, then combine them into a final score. In interaction analysis, we propose Targeted Node Centric-Degree Centrality (TNC-DC) which finds insects with many directly and indirectly connections to the virus. Finally, we integrate Wikidata, DBPedia, and NCBIOntology to provide comprehensive information about insect vectors in the knowledge extension stage. Results: The interaction graph for each test virus was created. At the test stage, interaction and taxonomic analysis achieved 0.80 precision. TNC-DC succeeded in overcoming the failure of the original degree centrality which always got bees in the prediction results. During knowledge extension stage, we succeeded in finding the natural enemy of the Bemisia Tabaci (an insect vector of Pepper Yellow Leaf Curl Virus). Furthermore, an insect vector search engine is developed. The search engine provides network analysis insights, insect vector common names, photos, descriptions, natural enemies, other species, and relevant publications about the predicted insect vector. Conclusion: An insect vector search engine correctly identified virus vectors using GloBI data, TNC-DC, and entity embedding. Average precision was 0.80 in precision tests. There is a note that some insects are best in the first-to-five order. Keywords: Knowledge Graph, Network Analysis, Degree Centrality, Entity Embedding, Insect Vector

Improving undergraduate education of occupational health and occupational medicine appling massive open online courses & problem-based learning

BackgroundThe learning of Occupational Health and Occupational Medicine in undergraduate college students in China has been hindered by various factors. This study aimed to explore the effects of the application of Massive Open Online Courses (MOOC) & Problem-based learning (PBL) in the learning of Occupational Health and Occupational Medicine in undergraduate college students in China.MethodsStudents enrolled in 2017 and 2018 were categorized in the control group and study group, and received PBL learning and MOOC + PBL learning, respectively. The effects of learning were assessed by scores of final exam, satisfaction degree of students, and feedbacks.ResultsThe mean score of the final exam was not significantly different between the two groups. However, the further comparison by levels of scores showed that the percentages of good and excellent were both significantly higher in the study group than control group. The overall satisfaction degree was significantly higher in the study group than control group. In addition, the scores of the 3 dimensions of satisfaction degree, i.e. learning preparation, learning process, and learning effect, were all significantly higher in the study group than control group. The feedbacks of the students showed that they thought MOOC + PBL learning could better improve the learning efficacy, despite a substantial proportion of students reported that MOOC + PBL learning more time-consuming.ConclusionsThe findings showed that the combination of MOOC and PBL in the learning of Occupational Health and Occupational Medicine is an effective method capable of improving the learning efficacy in college students of Prophylactic Medicine. Further efforts are needed to optimize the MOOC platform to provide a friendlier interface.

Validation of a Tool to Evaluate Nursing Students' Electronic Health Record Competency in Simulation.

The aim of the study was to establish reliability and validity of the Competency Assessment in Simulation of Electronic Health Records (CASE) tool. Effective teaching and learning practices, including valid and reliable assessment of students' electronic health record (EHR) competency, contribute to safe, high-quality, efficient nursing care. The study used a mixed-methods design to test reliability and validity of the CASE tool. A nationally representative sample of faculty from universities representing 27 states provided scores for videos using the CASE tool. Forty-seven participants completed the first scoring survey; 22 of the 47 participants (47%) completed the second-round scoring. Intraclass correlation for the final score between the first and second responses shows the consistency of test-retest reliability (ICC = .78, p < .001). The CASE tool provided evidence of validity and reliability in evaluating EHR competency in simulation.

Fuzzy Logic Method for Measuring Sustainable Decent Work Levels as a Corporate Social Responsibility Approach

The purpose of this study was to propose an interactive computer system that utilises the MATLAB Fuzzy Logic Designer to measure the level of implementation of SDG 8, which focuses on sustainable decent work (SDW) and economic growth. This study used policies and laws as parameters to determine the presence or absence of SDW. The fuzzy method was implemented in car windshield manufacturing in the auto parts industry as a case study to define and quantify work conditions and to determine the level of sustainable decent work (SDWL). The study described environmental conditions, such as noise, lighting, and heat stress; ergonomic factors, such as exposure time, the mass of the object manipulated, and lifting frequency; and organisation at work, such as workplace violence, salary, and workday, as linguistic variables. The level of the presence or absence of SDW was defined as their membership functions. The resulting vectors determined the absence of SDW with a score of 1.5 in two linguistic variables: environmental conditions and ergonomic factors. Some features of SDW in the linguistic variable organisation at work had an SDW score of 5. The SDWL vector determined a final score of 1.24, indicating the absence of decent work in production areas. This study found that the workers suffer a lack of long and healthy lives and a bad standard of living without economic growth due to work-related musculoskeletal disorders and work illnesses, increasing their out-of-pocket spending and catastrophic health expenses. As a CSR approach, assessing SDWLs helped managers improve policies and work conditions.

Sensory processing and engagement of autistic children in childhood routines

ABSTRACT: Background: Occupations constitute a foundation of human existence, however, the impairment of skills in processing sensory information can impact the engagement of children diagnosed with Autism Spectrum Disorder (ASD). Objective: to investigate the relationship between sensory processing and the engagement of autistic children with 2 to 5 years old in their routines. Method: a quantitative correlational study was carried out. Caregivers responses were collected through an online survey, employing a chain-referral sampling method with two questionnaires, the SPM-P (Sensory Processing Measure - Preschool - Home Form) and the CEQ (Children's Engagement Questionnaire). Results: a total of 56 respondent families [30 families with ASD children and 26 with typically developing (TD) children] were obtained. A correlation and multiple regression analysis identified that the final scores for sensory processing and engagement correlated inversely in ASD and TD children, and that ASD diagnosis and impaired Motor Planning and Ideas significantly reduced engagement, while higher age and schooling incresead it. Conclusion: we observed that the use of strategies that increase the child's engagement in their routines is essential to promote the acquisition of new skills for participation in daily life.

Exploring the potential of ChatGPT as an adjunct for generating diagnosis based on chief complaint and cone beam CT radiologic findings.

This study aimed to assess the performance of OpenAI's ChatGPT in generating diagnosis based on chief complaint and cone beam computed tomography (CBCT) radiologic findings. 102 CBCT reports (48 with dental diseases (DD) and 54 with neoplastic/cystic diseases (N/CD)) were collected. ChatGPT was provided with chief complaint and CBCT radiologic findings. Diagnostic outputs from ChatGPT were scored based on five-point Likert scale. For diagnosis accuracy, the scoring was based on the accuracy of chief complaint related diagnosis and chief complaint unrelated diagnoses (1-5 points); for diagnosis completeness, the scoring was based on how many accurate diagnoses included in ChatGPT's output for one case (1-5 points); for text quality, the scoring was based on how many text errors included in ChatGPT's output for one case (1-5 points). For 54N/CD cases, the consistence of the diagnosis generated by ChatGPT with pathological diagnosis was also calculated. The constitution of text errors in ChatGPT's outputs was evaluated. After subjective ratings by expert reviewers on a five-point Likert scale, the final score of diagnosis accuracy, diagnosis completeness and text quality of ChatGPT was 3.7, 4.5 and 4.6 for the 102 cases. For diagnostic accuracy, it performed significantly better on N/CD (3.8/5) compared to DD (3.6/5). For 54N/CD cases, 21(38.9%) cases have first diagnosis completely consistent with pathological diagnosis. No text errors were observed in 88.7% of all the 390 text items. ChatGPT showed potential in generating radiographic diagnosis based on chief complaint and radiologic findings. However, the performance of ChatGPT varied with task complexity, necessitating professional oversight due to a certain error rate.

The outcomes of team-based learning vs small group interactive learning in the obstetrics and gynecology course for undergraduate students.

Team-based learning (TBL) is a well-established active teaching method which has been shown to have pedagogical advantages in some areas such as business education and preclinical disciplines in undergraduate medical education. Increasingly, it has been adapted to clinical disciplines. However, its superiority over conventional learning methods used in clinical years of medical school remains unclear. The aim of this study was to compare TBL with traditional seminars delivered in small group interactive learning (SIL) format in terms of knowledge acquisition and retention, satisfaction and engagement of undergraduate medical students during the 6-week obstetrics and gynecology clerkship. The study was conducted at Karolinska Institutet, a medical university in Sweden, and had a prospective, crossover design. All fifth-year medical students attending the obstetrics and gynecology clerkship, at four different teaching hospitals in Stockholm (approximately 40 students per site), in the Autumn semester of 2022 were invited to participate. Two seminars (one in obstetrics and one in gynecology) were designed and delivered in two different formats, ie TBL and SIL. The student:teacher ratio was approximately 10:1 in the traditional SIL seminars and 20:1 in the TBL. All TBL seminars were facilitated by a single teacher who had been trained and certified in TBL. Student knowledge acquisition and retention were assessed by final examination scores, and the engagement and satisfaction were assessed by questionnaires. For the TBL seminars, individual and team readiness assurance tests were also performed and evaluated. Of 148 students participating in the classrooms, 132 answered the questionnaires. No statistically significant differences were observed between TBL and SIL methods with regard to student knowledge acquisition and retention, engagement and satisfaction. We found no differences in student learning outcomes or satisfaction using TBL or SIL methods. However, as TBL had a double the student to teacher ratio as compared with SIL, in settings where teachers are scarce and suitable rooms are available for TBL sessions, the method may be beneficial in reducing faculty workload without compromising students' learning outcomes.

Evaluating the performance of ChatGPT and Perplexity AI in Business Reference

The Thomas Mahaffey Jr. Business Library conducted a study to assess the performance of two competing generative AI products, ChatGPT and Perplexity AI, in answering business reference questions. The study used a data set consisting of a sample of anonymized reference questions submitted through the library’s ServiceNow ticketing system between January 2018 and May 2022. The questions were input as prompts to each competing AI. Responses were collected and evaluated by their performance in four separate dimensions relevant to business reference: accessibility, library referral, quality, and serendipity. Each dimension was scored on a 0-5 Likert scale resulting in a final composite performance score for each AI. Results showed similar and underwhelming performance between each AI at the composite level. Analysis of scores in each individual scoring dimension showed greater variance in the score distributions between the competing AI. Through the evaluation process, key strengths, weaknesses, and trends emerged between each AI. The study provides a quantitative measure of where generative AI stands in its capabilities in a business library reference context, and it recommends, based on the results of the evaluation, making use of generative AI in its current iteration as a supplementary tool for business reference as opposed to considering it as a replacement.

Artificial intelligence: ChatGPT as a disruptive didactic strategy in dental education.

To evaluate the influence of ChatGPT on academic tasks performed by undergraduate dental students. Fifty-five participants completed scientific writing assignments. First, ChatGPT was utilized; subsequently, a conventional method involving the search of scientific articles was employed. Each task was preceded by a 30-min training session. The assignments were reviewed by professors, and an anonymous questionnaire was administered to the students regarding the usefulness of ChatGPT. Data were analyzed by Mann-Whitney U-test. Final scores and scores for the criteria of utilization of evidence, evaluation of arguments, and generation of alternatives achieved higher values through the traditional method than with ChatGPT (p=0.019, 0.042, 0.017, and <0.001, respectively). No differences were found between the two methods for the remaining criteria (p>0.05). A total of 64.29% of the students found ChatGPT useful, 33.33% found it very useful, and 3.38% not very useful. Regarding its application in further academic activities, 54.76% considered it useful, 40.48% found it very useful, and 4.76% not very useful. A total of 61.90% of the participants indicated that ChatGPT contributed to over 25% of their productivity, while 11.9% perceived it contributed to less than 15%. Concerning the relevance of having known ChatGPT for academic tasks, 50% found it opportune, 45.24% found it very opportune, 2.38% were unsure, and the same percentage thought it is inopportune. All students provided positive feedback. Dental students highly valued the experience of using ChatGPT for academic tasks. Nonetheless, the traditional method of searching for scientific articles yield higher scores.