Student-centered teaching practices such as active learning continue to gain momentum in college science education. Many instructors committed to these innovative practices transform their classroom beyond the standard lecture. Nevertheless, widespread implementation of these practices is limited because the learning benefits for students are often attained through increased instructional complexity to which many instructors cannot commit. When co-instructors are teaching the course, the level of commitment to building a student-centered classroom may be even more profound. For these reasons, new tools are needed to help instructors and co-instructors plan, organize, evaluate, and communicate their classroom innovations. Pathway modeling is a tool with potential to fill this gap. Unlike curriculum mapping -- which identifies academic content gaps, redundancies, and misalignments by examining a series of courses within a plan of study – course pathway modeling creates a visual map of a single course and reveals how teaching practices influence short-, mid-, and long-term student learning outcomes. This essay demonstrates how course pathway modeling can help co-instructors better represent the complexity of student-centered teaching practices. We include guides for creating course pathway models and discuss how this approach offers the potential to improve curricular design, course evaluation, student assessment, and communication between co-instructors.

University course scheduling (UCS) is one of the most important and time-consuming issues that all educational institutions face yearly. Most of the existing techniques to model and solve UCS problems have applied approximate methods, which are different in terms of efficiency, performance, and optimization speed. Accordingly, this research aims to apply an exact optimization method to provide an optimal solution to the course scheduling problem. In other words, in this research, an integer programming model is presented to solve the USC problem. In this model, hard and soft constraints include the facilities of classrooms, courses of different levels and compression of students' curriculum, courses outside the faculty and planning for them, and the limited time allocated to the professors. The objective is to maximize the weighted sum of allocating available times to professors based on their preferences in all periods. To evaluate the presented model's feasibility, it is implemented using the GAMS software. Finally, the presented model is solved in a larger dimension using a real data set from a college in China and compared with the current program in the same college. The obtained results show that considering the mathematical model's constraints and objective function, the faculty courses' timetable is reduced from 4 days a week to 3 working days. Moreover, master courses are planned in two days, and the courses in the educational groups do not interfere with each other. Furthermore, by implementing the proposed model for the real case study, the maximum teaching hours of the professors are significantly reduced. The results demonstrate the efficiency of the proposed model and solution method in terms of optimization speed and solution accuracy.

Recently on the December 4, 2021 at 03:00 PM, 3676 m high Mount Semeru located in the East parts of Java Island has erupted. To our best knowledge, an immediate and rapid systematic analysis of the volcanic ash plume courses, PM_2.5 emissions, and environmental impacts based on Mount Semeru eruption has not been implemented so far. Then, this research aims to provide and fill the research gap on the rapid assessment of recent Mount Semeru eruption. From the result, it is clearly visible that for 12 hours the volcanic ash plume course was eastward. The volcanic ash plume can travel a distance of 0–10 km to the North and South directions, and more than 10 km to the East direction. The size of the volcanic ash plume was large at 02:00 AM on December 5, 2021. The smallest size of a volcanic ash plume was recorded at 09:00 PM on December 4, 2021. Most parts of the ash plume (55.98%) or equals 39.01 km² contain fallen volcanic material amounts ranged from 1 kg/m² to 10 kg/m². The fallen volcanic material amount peaked between 08:00 PM and 11:00 PM. Based on the estimation, the PM_2.5 content in the atmosphere increased after the eruption. The mean of PM_2.5 before the eruption was 48.5 ± 19.3(95%CI: 29.2 to 67.8 ug/m³). While after eruption the mean of PM_2.5 was 79.4 ± 32.2(95%CI: 47.2 to112 ug/m³). It indicated that the Mount Semeru eruption has increased the PM_2.5 equals 63.65%.

The National Examination in Indonesia has been abolished since 2020. Hence, the Indonesian junior high schools makes its final examination items for the 9th-grade, and from the results, the school determines students' graduation. The final examination has an important role and significant value in making decisions about students' graduation. Therefore, this study is aimed to analyze the Online Final Examination items in one of the public junior high schools in Bandung. The sample was 234 students in grade 9 using their mathematics examination tests, comprising 20 multiple-choice items with 4 options, while the data processing used Winsteps software with the Rasch modeling technique. Subsequently, the Rasch model results showed an acceptable person separation statistic of 1.54 and sufficient person reliability at 0.74. The item separation statistics was in a good category at 4.59, while the item reliability at 0.95 was excellent. Although four online final examination items were in the fit category, 16 were good and capable of dividing students according to their abilities. The result also provided very detailed data about the quality of the items and the ability of each grade 9 student. Since each test item is included in the fit category, this study contributes information on preparing and analyzing the Online Final Examination to teachers..

The kiwiberry is a trendy variety that shows a high demand for consumption but presents commercialization challenges due to its short life. The purpose of this study is to compare the effects of edible alginate coatings in prolonging the shelf life of this fruit. Two different forms were tested (coarse emulsions(C) and nanoemulsions(N)) and the effects of two different coating application techniques (spraying(S) and dipping(D)) were tested. Additionally, the use of Vis-NIR for quality monitorization was assessed as well. Fruits were treated with ten different treatments, using the following base formulations:Alginate(AL) 2%(w/v) enriched with eugenol(Eug) and citral(Cit) at minimum inhibitory concentrations (0.10% and 0.15%) and double MIC. Samples were taken from cold storage (0° C), at 2 and 4 weeks. For fruit quality evaluation, colour analysis, firmness, soluble solids content, dry matter and weight loss were performed. During storage, the colour and SSC parameters increased. Firmness decreased over time.Weight loss was the parameter with higher significant differences, increasing over time and more pronounced in treatments with higher essential oils components. This study suggests that AL-S, AL-D, AL-Cit 0.15+Eug0.1-N-S, AL-Cit0.15+Eug0.1-N-D and AL-Cit0.15+Eug0.1-C-D can preserve kiwiberries quality. Moreover, we verify that the Vis-NIR spectral analysis could be beneficial for performing coatings discrimination.

In this contribution, time course studies were performed toward oxidation of different peroxidase substrates in the presence of silver nanozymes. In this regard, two common peroxidase substrates, TMB and DAB, were selected as model chromogens. The process of the oxidation reaction was probed by recording the absorbance of the colored products using UV-Vis spectrophotometer. Thereafter, the nanozymatic activity was calculated and used as an index for comparing the performance of the silver nanozymes against different substrates in a certain reaction time. The time course curves, revealed that the maximal activity of the silver nanozymes were achieved after a very short time of 3.0 min toward TMB oxidation while regarding DAB, the maximal activity was observed after 25.0 min which is 6.5-fold slower than that of the TMB oxidation. The difference between the DAB and TMB can be assigned to their different reaction pathways and different reactivity. In fact, the oxidation of DAB has occurred via n-electron irreversible pathway while the TMB oxidation has occurred through a simple 2-electon reversible pathway. Besides, DAB is a high stable and less relative compound compared of TMB, resulting different oxidation times, different affinity for binding to nanozyme active nodes which lead to different nanozymatic activities.

Course-based undergraduate research experiences (CUREs) provide students with opportunities for the same gains that apprenticed research with faculty members offer. As their popularity increases, it is important that critical elements of CUREs are supported by thoughtful design. Student experiences in CUREs can provide important insights into why CUREs are so effective. We present evidence from students who participated in CUREs at the introductory, intermediate, and advanced levels, as well as from graduate teaching assistants for an introductory lab course that included a CURE. Students and teaching assistants describe repetition as a valuable element in CUREs and other laboratory experiences. We used student work and open-ended interviews to identify which of five previously described elements of CUREs students found important. Because repetition was particularly salient, we characterized how students described repetition as they experienced it in courses that contained full-length or “micro”-CUREs. In prompted interviews, students described how repetition in CUREs provided cognitive (learning concepts) and practical (learning technical skills) value. Recent graduates who had participated in CUREs at each level of their Biology education were particularly aware that they placed value in repetition and acknowledged it as motivational in their own learning. Many students described repetition in metacognitive terms, which also suggests that as students advance through laboratory and CURE curricula, their understanding of how repetition supports their learning becomes more sophisticated. Finally, we integrated student descriptions to suggest ways in which repetition can be designed into CUREs or other laboratory courses to support scientific learning and enhance students’ sense of scientific identity.

This paper outlines evidence-based practice in the context of professionalism, and highlights the contribution evidence-based practice can make to the professional practice of higher education course managers. Implications of the changing HE landscape for the status of academics as professionals are reviewed, and evidence-based practice is proposed as a solution for both enhanced course management and to remedy perceived deprofessionalisation. Finally, questions regarding researching professional practice within one’s own institution are addressed.

The aim of the present study is to investigate both the performance and preferences of males and females Computer Science (CS) graduates. In order to attain the above goal, a quantitative case study was conducted regarding 89 degrees, acquired from 2006 to 2012, from the Department of Computer Science and Technology, University of Peloponnese, Greece. The analysis of the data revealed that in terms of performance, no significant differences between the mean grades of males and females exist, in almost most of the courses included in the curriculum of the aforementioned CS department. Any statistically significant differences in performances were present in almost equal number of courses in favor of males and females. It seems also, that females performed better in the courses they selected more than males. Regarding preferences, in CS courses, it seems that gender differences are existent. Males preferred more than females did core programming courses and advanced topics of Software Systems, computer networks, computer engineering, robotics and mathematics, whereas females preferred more the study of algorithms and security issues, computer fractals, data management, computer architecture, and mobile communication. In addition, females preferred courses in reference with humanities and social sciences, CS terminology, and career opportunities. Yet, females did not select any of programming lab-based courses, computer engineering, computer network issues and robotics.

African swine fever (ASF) is one of the most important and devastating viral diseases in wild boar and domestic pigs worldwide. In the absence of vaccines or treatment options, early clinical detection is key and requires sound knowledge of disease characteristics. To provide practitioners and state veterinarians with detailed information, the objective of the present study was to characterize the ASF virus (ASFV) isolate “Belgium 2018/1” in subadult and weaning domestic pigs. To this end, two animal trials were performed. Trial A included eight subadult domestic pigs and trial B five weaner pigs. In general, clinical signs and pathological lesions were in line with previous studies utilizing highly virulent ASF genotype II viruses. However, in trial A, four subadult domestic pigs survived and recovered pointing to an age dependent outcome. The long-term fate of those survivors remains under discussion and would need further investigations.

In this paper, we address the following research question: Is feasibility to use an artificial intelligence system to predict the risk of student failure in a course based solely on their performance in prerequisite courses? Adopting a machine learning-based quantitative approach, we implement Course Prophet, the prototype of a predictive system that maps the input variables representing student performance to the target variable, i.e., the risk of course failure. We evaluate multiple machine learning methods and find that the Gaussian process with Matern kernel outperforms other methods, achieving the highest accuracy and a favorable trade-off between precision and recall. We conduct this research in the context of the students pursuing a Bachelor’s degree in Systems Engineering at the University of Córdoba, Colombia. In this context, we focus on predicting the risk of failing the Numerical Methods course. In conclusion, the main contribution of this research is the development of Course Prophet, providing an efficient and accurate tool for predicting student failure in the Numerical Methods course based on their academic history in prerequisite courses.

The key to building a strong bridge country lies in talent, and the foundation lies in education. The cultivation of bridge engineering talents is related to the future and destiny of building a strong bridge country. This course adopts the educational philosophy of "holographic teaching method" centered on the comprehensive development of students, cultivating "engineering thinking" guided by engineering education certification, enhancing "abilities and qualities" through professional knowledge, reconstructing the course knowledge content system through engineering philosophy thinking, and implementing the ideological and political construction of the course in a multi-level unified manner of "explicit + implicit". Based on restructuring the course content system, we will strengthen the construction of diversified course resources, integrate theory with practice throughout the entire process of the course, practice the concept of "bridge architects + bridge engineers" parallel development, and cultivate cross-border and compound talents with comprehensive qualities of "engineering + art + humanities".

Abstract—Online learning platforms provide diverse course resources, but this often result in the issue of information overload. Learners always want to learn courses that are appropriate for their knowledge level and preferences quickly and accurately. Effective course recommendation plays a key role in helping learners select appropriate courses and improving the efficiency of online learning. However, when a user is enrolled in multiple courses, Existing course recommendation methods face the challenge in accurately recommending the target course that is most relevant to the user, because of the noise courses. In this paper, we propose a novel reinforcement learning model named Actor-Critic Hierarchical Reinforcement Learning (ACHRL). The model incorporates the Actor-Critic method to construct the profile reviser. This can remove noise courses and make personalized course recommendation effectively. Furthermore, we propose a policy gradient based on temporal difference error to reduce the variance in the training process, to speed up the convergence of the model, and improves the accuracy of the recommendation. We evaluate the proposed model on two real datasets, and the experimental results show that the proposed model is significantly outperforms the existing recommendation models (improving 3.77% to 13.66% in terms of HR@5).

Gene editing tools such as CRISPR-Cas9 have created unprecedented opportunities for genetic studies in plants and animals. We designed a course-based undergraduate research experience (CURE) to train introductory biology students in the concepts and implementation of gene editing technology as well as develop their soft skills in data management and scientific communication. We present two versions of the course that can be implemented with twice-weekly meetings over a five-week period. In the remote-learning version, students perform homology searches, design guide RNAs and primers, and learn the principles of molecular cloning. This version is appropriate when access to laboratory equipment or in-person instruction is limited, such as closures that have occurred in response to the Covid-19 pandemic. In the in-person version, students design guide RNAs, clone CRISPR-Cas9 constructs, and perform genetic transformation of the model plant Arabidopsis thaliana. The highly parallel nature of the CURE makes it possible to target dozens to hundreds of genes, depending on the number of course sections available. Applying this approach in a sensitized mutant background enables focused reverse genetic screens for genetic suppressors or enhancers. The course can be readily adapted to other organisms or projects that employ gene editing.

During the last decades, a growing number of studies have shown that infections during pregnancy have an important impact on both pregnant women and their fetuses. Our goal was to identify newborns from pregnancies with SARS-CoV-2 infection and to investigate the extension of neonatal complications using cardiac, abdominal and cerebral ultrasonography, hearing testing and indirect ophthalmoscopy. By contrast, neonates whose mothers were vaccinated against COVID-19 during pregnancy and those from pathology-free pregnancies have been examined. A total of 458 newborns were included, over a period of 10 months, divided into 3 groups, COVID-19 group, vaccine group and control group. Although 6 cardiac malformations were found in the COVID-19 group, no correlation was made compared to the vaccine and control group (p=0.07). Grade 1 intraventricular hemorrhage and hypoxic ischemic encephalopathy were the most prevalent among neonates from mothers with SARS-CoV-2 infection (p=0.002 and p<0.001, respectively). The kidney anomaly found to be most frequent in this group was grade 1 unilateral hydronephrosis (p<0.001). COVID-19 disease during the gestational period had no effect on the auditory or visual function. Despite the fact that our observations are relevant, further studies investigating the effects of SARS-CoV-2 infection during pregnancy and the neonatal outcomes are necessary.

Course-based Undergraduate Research Experiences (CUREs) provide the same benefits as individual, mentored faculty research while expanding the availability of research opportunities. One important aspect of CUREs is student’s engagement in collaboration. We developed a partnership with the Caenorhabditis elegans (C. elegans) database, WormBase, in which students submitted annotations of published manuscripts to the website. This activity provided students with a collaborative research activity that benefitted the greater scientific community and enhanced students’ understanding of molecular genetics during the COVID-19 pandemic. WormBase relies on community annotators to read published articles and input phenotypic data. Students submitted a total of nine annotations directly to WormBase, which were curated by WormBase to ensure correctness and to reduce overlap from redundant annotations. Due to the stress on students during this time of crisis, qualitative data were collected in lieu of quantitative pre-post analyses. Students described their learning experiences in terms of interactions with the scientific community and the “real world”, content knowledge and competencies, and changes in perspectives and use of resources. Students also reported that this activity was helpful in their understanding of critical molecular genetics concepts. Most students reported on cognitive processes that represent mid-level Bloom’s categories. The shift to online learning during the COVID-19 pandemic created an immediate need for meaningful, collaborative experiences in CUREs. By partnering with WormBase, students gained insight into the scientific community and contributed as community members. We describe possible modifications for future courses, potential expansion of the WormBase collaboration, and future directions for quantitative analysis.

Algorithms, indispensable to understand Artificial Intelligence (AI), are omnipresent in social media but users’ understanding of these computational processes and the way they impact their consumption of information is often limited. There is a need for Media and Information Literacy (MIL) research investigating a) how MIL can support Algorithm Literacy (AL) as a subset of competences, and with what working definition, b) what competences users need in order to evaluate algorithms critically and interact with them effectively, and c) how to design learner-centred interventions that foster increased user understanding of algorithms and better response to disinformation spread by such processes. Based on Crossover project research, this paper looks at four scenarios of use by journalists, developers and MIL experts that mirror users’ daily interactions with social media. The results suggest several steps towards integrating AL within MIL goals, while providing a concrete definition of Algorithm-literacy that is experience-based. The competences and design considerations are organised in a conceptual framework thematically derived from the experimentation. This contribution can support AI developers and MIL educators in their co-design of algorithm-literacy interventions and guide future research on AL as part of a set of nested AI literacies within MIL.

In systems biology, biological phenomena are often modeled by ODE and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulations, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the SBSCL, and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code available from https://github.com/TakahiroYamada/SBMLWebApp. The program runs online at http://simulate-biology.org.

Objective: Determine the feasibility of utilizing longitudinal electronic dental record (EDR) data to track change over time in patient periodontal disease (PD) and to generate three patient cohorts: 1) patients whose disease did not change over time, 2) patients whose PD progressed, and 3) patients whose disease improved over time using informatics approaches. Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between January 1, 2009, and December 31, 2014, at the Indiana University School of Dentistry (IUSD) clinics. We developed and tested three automated computer applications to: 1) diagnose periodontitis cases from periodontal charting, 2) retrieve clinician-documented diagnoses from clinical notes, and 3) track disease change over time. We also evaluated the density of longi-tudinal EDR data for the following follow-up times: 1) none, 2) up to 5 years, 3) >5 and <=10 years, and 4) >10 and <=15 years Results: Thirty-four percent (n=9,954) of the study cohort had up to five years of follow-up visits with an average of 2.78 visits with periodontal charting information. An average of three patient visits per year that contained periodontal charts (63,552) were utilized to obtain a diagnosis, which is considered excellent. For clinician-documented diagnoses from clinical notes, 42% of patients (n=5,562) had at least two PD diagnoses to determine their disease change. In this cohort with cli-nician-documented diagnoses, 72% percent of patients (n=3,919) did not have a disease status change between their first and last visits, 669 (13%) patients' disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We found excellent longitudinal data when diagnoses generated from periodontal charting were considered (three visits per pa-tient). This information can be now utilized for studying the clinical course of periodontitis.

In this paper I tentatively answer 50 questions sampled from a pool of over 10,000 weekly questions formulated by students in a course entitled “The Self”. The questions pertain to various key topics about self-processes, such as self-awareness, self-knowledge, self-regulation, self-talk, self-esteem, and self-regulation. The students’ weekly questions and their answers highlight what is currently know about the self. Answers to the student questions also allow for the identification of some recurrent lessons about the self. Some of these lessons include: all self-processes are interconnected (e.g., prospection depends on autobiography), self-terms must be properly defined (e.g., self-rumination and worry are not the same), inner speech plays an important role in self-processes, controversies are numerous (are animals self-aware?), measurement issues abound (e.g., self-reflection as an operationalization of self-awareness), deficits in some self-processes can have devastating effects (e.g., self-regulatory deficits may lead to financial problems), and there are lots of unknowns about the self (e.g., gender differences in Theory-of-Mind).

Aptamers have a well-earned place in therapeutic, diagnostic, and sensor applications, and we now show that they provide an excellent foundation for education, as well. Within the context of the Freshman Research Initiative (FRI) at The University of Texas at Austin, students have used aptamer selection and development technologies in a teaching laboratory to build technical and 21st century skills appropriate for research scientists. One of the unique aspects of this course-based undergraduate research experience is that students develop their own projects, and take ownership of their own science in what would otherwise be a traditional teaching lab setting. Of the many successes, this work includes the isolation and characterization of novel calf intestinal alkaline phosphatase (anti-CIAP) RNA aptamers by an undergraduate researcher. Further, preliminary survey data suggest that students who participate in the aptamer research experience express significant gains in their self-efficacy to conduct research, and their perceived ability to communicate scientific results, as well as organize and interpret data. This work will describe the use of aptamers in an educational setting, highlight the positive student outcomes of the aptamer research experience, and more particularly present the research findings relative to the anti-CIAP aptamer.

This comprehensive study delves into the implementation and effectiveness of the flipped classroom model in engineering EMI (English as a Medium of Instruction) courses in Taiwan. Situated within the strategic framework of Taiwan's Bilingual Nation 2023 policy, this research aims to enhance the global competitiveness of Taiwan's semiconducting manufacturing engineering sector. The study’s primary focus is on understanding the perceptions and learning outcomes of EFL (English as a Foreign Language) students in engineering courses. Through a methodical approach using descriptive statistics and chi-square tests, the study analyzes data from 33 junior engineering students specializing in mechanical and mechatronic fields. The findings highlight a significant positive influence of the flipped classroom model on various aspects of student learning, including increased engagement, heightened creativity, and enhanced problem-solving skills. Additionally, the study emphasizes the critical role of timely L1 support in facilitating effective learning in EMI settings. These outcomes not only demonstrate the flipped classroom's viability as a sustainable educational approach but also provide crucial insights for educators and policymakers. By aligning cutting-edge teaching methods with the evolving needs of engineering education, this study contributes to the discourse on educational innovation. It ultimately guides the development of future engineering programs that cater to diverse student needs and fosters the cultivation of skilled engineering professionals.