Search results for: mathematical learning activities

Authors: Alhassan Dramani Yakubu

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The primary purpose of this study was to analyze effects that participating in sporting activities has on academic performance among students at Yaa Asantewaa Girls’ Senior High School. To dig out the main objective of the study, descriptive survey design was employed. The study used 45 respondents comprising of 25 student – athletes and 20 non-student – athletes. The purposive sampling and stratified random sampling technique were used to sample population of 455 students involved. The academic performance of sports participants is compared with those of non – participants in terms of their outcomes in the form of grades from mathematics. Data was obtained from the sample by the use of questionnaire which was self - administered. The questionnaire sought information on level of student’s participation in sports and importance of sports participation to students. Results revealed that participation in sporting activities is associated with higher grades among students. The analysis reinforces the idea that apart from their health benefits for participants, sporting activities lead to the attainment of the performance goals to which higher institutions aspire. The findings also implies that, mathematics teachers and other subject teachers should not fend off students from participating in sporting activities with the trepidation that participating in sports inflame academic performance. This study recommend that, educational programs about sports should be provided for students’ through the educational system to bring about positive academic performance.

Keywords: physical activity, physical education, intra mural, extra mural

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Jožef Ritonja

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The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: biochemical reactor, fermentation process, modelling, adaptive control

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Authors: Makhim Artikova, Shavkat Duschanov

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So far, there have been a plethora of attempts to improve learners’ academic writing skills. However, this issue remains to be a real concern among the majority of students, especially those who are standing on their academic life threshold. The purpose of this research is improving students’ academic writing skills through 'Questions and Answer Reading' activities. Using well-prepared and well-chosen reading materials (from textbooks, scientific journals, or magazines) and applying questions and answer activities in the classroom facilitate learners to become great critical readers. Furthermore, it boosts their writing skills, which are the most crucial part of students’ personal and academic developments. In this activity, the class is divided into small groups of four. Then, the instructor will give students whether one section of the text or full text asking them to read and to find unfamiliar words within the group. After discovering the meaning of unknown words, each group has to share their findings with the class. In the next stage of the activity, students should be asked to create questions in a group based on the given reading material. Follow by each group should ask the other groups their questions which are an excellent opportunity to challenge leads to improve critical thinking skills. In the last part, the students are asked to write the text or article summary, which is the activity core that pilots to the writing skills perfection. This engaging activity highlights the effectiveness of incorporating reading materials into the classroom when it comes to improving students’ composition writings. Structural writing after every reading activity resulted in improving students’ coherence and cohesion in writing well-organized essays. Having experimented with high school 9th and 11th-grade students, implementing reading activities into the classroom is proved to be a productive tool to enhance one’s academic writing skills. In the future, this method planning to be implemented among university students.

Keywords: academic writing, coherence and cohesion, questions and answer activities, scientific reading

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Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

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A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: climbing stairs, FSBLC, ILC, service robot

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Authors: Thomas Ejobowah Boye, Philip Oghenetega Ekpon

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The paper examines the availability and the utilization of recreational facilities for prison inmate’s rehabilitation in Nigeria. In order to carry out the study the researchers visited sampled prisons in the six geo-political zones in Nigeria. Instant assessment of available recreational facilities was carried out. Inmates were asked to tick a self-design questionnaire that was validated by experts in the Departments of Physical and Health Education, Delta State University and the College of Physical Education, Mosogar on available recreational facilities and activities engaged in by them. The data collected was subjected to percentage analysis. The study revealed that there is little or no standard recreational facilities in all the prisons visited. Considering the role physical activities play in the overall development of individuals physically, mentally, emotionally, morally, and socially it was recommended that the authorities of the Nigerian prisons should as a matter of urgency include recreational activities as a means of reforming and rehabilitating prison inmates. To achieve the desire to rehabilitate prison inmates the researchers also recommended that facilities and equipment should be made available in all prisons in Nigeria.

Keywords: facility, prison, recreation, rehabilitation

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Authors: Remus Titiriga

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The paper focuses on Pascal's indivisibles evolving to Leibniz's infinitesimals. It starts with parallel developments by the two savants in Combinatorics (triangular numbers for Pascal and harmonic triangles for Leibniz) and their implication in determining the sum of mathematical series. It follows with a focus on the geometrical contributions of Pascal. He considered the cycloid and other mechanical curves the epitome of geometric comprehensibility in a series of challenging problems he posed to the mathematical world. Pascal provided the solutions in 1658, in a volume published under the pseudonym of Dettonville, using indivisibles and ratios between curved and straight lines. In the third part, the research follows the impact of this volume on Leibniz as the initial impetus for the elaboration of modern calculus as an algorithmic method disjoint of geometrical intuition. Then paper analyses the further steps and proves that Leibniz's developments relate to his philosophical frame (the search for a characteristic Universalis, the consideration of principle of continuity or the rule of sufficient reason) different from Pascal's and impacting mathematical problems and their solutions. At this stage in Leibniz's evolution, the infinitesimals replaced the indivisibles proper. The last part of the paper starts with speculation around "What if?". Could Pascal, if he lived more, accomplish the same feat? The document uses Pascal's reconstructed philosophical frame to formulate a positive answer. It also proposes to teach calculus with indivisibles and infinitesimals mimicking Pascal and Leibniz's achievements.

Keywords: indivisibles, infinitesimals, characteristic triangle, the principle of continuity

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Authors: Marwa Hanafy

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The objective of linking the museum with school curriculum is to focus on the values and principles of the educational standards of the fourth grade as "equality, cooperation, allegiance, belonging, participation, peace, tolerance, pride and patriotism, etc." through activities, discussion, exhibits, etc., which can help the students to develop their characters and be useful for their society. For example, there is a lesson in Module 3 assess the role of women as mothers and queens, here this research will focus on the value of women and respect them through statues or images of women which support and affect positively on the students who will apply these Morals to themselves and to the community by dependency. It cannot be denied that the students have to be a part of the museum educational programs which have designed for them, by giving them the opportunity to participate, talk, discuss and express their opinions and hear them in the museums, this may be an effective way to confirm that the interests of children are taken into account.

Keywords: museum education, primary school education, school curriculum, informal learning

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Authors: Muhalim Muhalim

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Drawing on Lakoff’s theory of metaphor conceptualization, this article explores the conceptualization of language two writing (L2W) of ten students-teachers in Indonesia via metaphors. The ten postgraduate English language teaching students and at the same time (former) English teachers received seven days of intervention in teaching and learning L2. Using introspective log and focus group discussion, the results illuminate us that all participants are unanimous on perceiving L2W as process-oriented rather than product-oriented activity. Specifically, the metaphor conceptualizations exhibit three categories of process-oriented L2W: deliberate process, learning process, and problem-solving process. However, it has to be clarified from the outset that this categorization is not rigid because some of the properties of metaphors might belong to other categories. Results of the study and implications for English language teaching will be further discussed.

Keywords: metaphor conceptualisation, second language, learning writing, teaching writing

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: Ailene B. Anonuevo

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The aim of the study was to evaluate the quality of life presently available for the IP students in selected schools in the Division of Panabo City. This further explores their future dreams and current status in classes and examines some implications relative to their studies. The study adopted the mixed methodology and used a survey research design as the operational framework for data gathering. Data were collected by self-administered questionnaires and interviews with sixty students from three schools in Panabo City. In addition, this study describes the learners’ background and school climate as variables that might influence their performance in school. The study revealed that an IP student needs extra attention due to their unfavorable learning environment. The study also found out that like any other students, IP learners yearns for a brighter future with the support of our government.

Keywords: IP learners, learning landscape, school climate, quality of life

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Cindy Davis

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Higher education is changing globally and there is increasing pressure from professional social work accreditation bodies for academic programs to demonstrate how students have successfully met mandatory graduate competencies. As professional accreditation organizations increase their demand for evidence of graduate competencies, strategies to document and recording learning outcomes becomes increasingly challenging for academics and students. Studies in higher education have found support for the pedagogical value of ePortfolios, a flexible personal learning space that is owned by the student and include opportunity for assessment, feedback and reflection as well as a virtual space to store evidence of demonstration of professional competencies and graduate attributes. Examples of institutional uses of ePortfolios include e-administration of a diverse student population, assessment of student learning, and the demonstration of graduate attributes attained and future student career preparation. The current paper presents a case study on the introduction of ePortfolios for social work graduates in Australia as part of an institutional approach to technology-enhanced learning and e-learning. Social work graduates were required to submit an ePortfolio hosted on PebblePad. The PebblePad platform was selected because it places the student at the center of their learning whilst providing powerful tools for staff to structure, guide and assess that learning. The ePortofolio included documentation and evidence of how the student met each graduate competency as set out by the social work accreditation body in Australia (AASW). This digital resource played a key role in the process of external professional accreditation by clearly documenting and evidencing how students met required graduate competencies. In addition, student feedback revealed a positive outcome on how this resource provided them with a consolidation of their learning experiences and assisted them in obtaining employment post-graduation. There were also significant institutional factors that were key to successful implementation such as investment in the digital technology, capacity building amongst academics, and technical support for staff and students.

Keywords: accreditation, social work, teaching, technology

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Authors: Theodorou Kyriaki, Ypsilantis George

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Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: Tanja Kreitenweis

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Lifelong learning is increasingly seen as essential for coping with the rapidly changing work environment. To this end, serious games can provide convenient and straightforward access to complex knowledge for all age groups. However, learning achievements depend largely on a learner’s non-cognitive skill disposition (e.g., motivation, self-belief, playfulness, and openness). With the aim of combining the fields of serious games and non-cognitive skills, this research focuses in particular on the use of a business simulation, which conveys change management insights. Business simulations are a subset of serious games and are perceived as a non-traditional learning method. The presented objectives of this work are versatile: (1) developing a scale, which measures learners’ knowledge and skills level before and after a business simulation was played, (2) investigating the influence of non-cognitive skills on learning in this business simulation environment and (3) exploring the moderating role of team preference in this type of learning setting. First, expert interviews have been conducted to develop an appropriate measure for learners’ skills and knowledge assessment. A pretest-posttest experimental design with German management students was implemented to approach the remaining objectives. By using the newly developed, reliable measure, it was found that students’ skills and knowledge state were higher after the simulation had been played, compared to before. A hierarchical regression analysis revealed two positive predictors for this outcome: motivation and self-esteem. Unexpectedly, playfulness had a negative impact. Team preference strengthened the link between grit and playfulness, respectively, and learners’ skills and knowledge state after completing the business simulation. Overall, the data underlined the potential of business simulations to improve learners’ skills and knowledge state. In addition, motivational factors were found as predictors for benefitting most from the applied business simulation. Recommendations are provided for how pedagogues can use these findings.

Keywords: business simulations, change management, (experiential) learning, non-cognitive skills, serious games

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Authors: Teh Kean Kheng, Low Soon Yee, Burra Venkata Durga Kumar

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In 2022, as the future world becomes increasingly computer-related, more individuals are attempting to study coding for themselves or in school. This is because they have discovered the value of learning code and the benefits it will provide them. But learning coding is difficult for most people. Even senior programmers that have experience for a decade year still need help from the online source while coding. The reason causing this is that coding is not like talking to other people; it has the specific syntax to make the computer understand what we want it to do, so coding will be hard for normal people if they don’t have contact in this field before. Coding is hard. If a user wants to learn bash code with bash prompt, it will be harder because if we look at the bash prompt, we will find that it is just an empty box and waiting for a user to tell the computer what we want to do, if we don’t refer to the internet, we will not know what we can do with the prompt. From here, we can conclude that the bash prompt is not user-friendly for new users who are learning bash code. Our goal in writing this paper is to give an idea to implement a user-friendly Bash prompt in Ubuntu OS using Artificial Intelligent (AI) to lower the threshold of learning in Bash code, to make the user use their own words and concept to write and learn Bash code.

Keywords: user-friendly, bash code, artificial intelligence, threshold, semantic similarity, lexical similarity

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Authors: Murray Olowa

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This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

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Authors: Jennifer Nutton, Gayle Ployer, Ky Scott, Jenny Morgan

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Working in a circle within higher education creates a decolonial space of mutual respect, responsibility, and reciprocity that facilitates collaborative learning and deep connections among learners and instructors. This approach is beyond simply facilitating a group in a circle but opens the door to creating a sacred space connecting each member to the land, to the Indigenous peoples who have taken care of the lands since time immemorial, to one another, and to one’s own positionality. These deep connections not only center human knowledges and relationships but also acknowledges responsibilities to land. Working in a circle as a relational pedagogical praxis also disrupts institutional power dynamics by creating a space of collaborative learning and deep connections in the classroom. Inherent within circle work is to facilitate connections not just academically but emotionally, physically, culturally, and spiritually. Recent literature supports the use of online talking circles, finding that it can offer a more relational and experiential learning environment, which is often absent in the virtual world and has been made more evident and necessary since the pandemic. These deeper experiences of learning and connection, rooted in both knowledge and the land, can then be shared with openness and vulnerability with one another, facilitating growth and change. This process of beginning with the land is critical to ensure we have the grounding to obstruct the ongoing realities of colonialism. The authors, who identify as both Indigenous and non-Indigenous, as both educators and learners, reflect on their teaching and learning experiences in circle. They share a relational pedagogical praxis framework that has been successful in educating future social workers, environmental activists, and leaders in social and human services, health, legal and political fields.

Keywords: circle work, relational pedagogies, decolonization, distance education

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Authors: Thien Van Ngo

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The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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Authors: So Yae Koh, YeonWoo Song, Ji-Yeon Ryu, Jeong Yong Moon, Somi Kim Cho

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Blueberry, a perennial shrub, is one of the most popular fruits due to its flavor and strong free radical scavenging properties. In this study, the blueberry puree was fermented by Lactobacillus plantarum CK10 and the antioxidant activities of fermentation products were examined. Various conditions with different supplements (5% sucrose or 10% skim milk) were evaluated for fermentation efficiency and the effects on antioxidant properties. The viable cell count of lactic acid bacteria, pH, total phenolic compounds and flavonoids contents were measured after 7 days of fermentation. DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS [2,2’-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid)] radical scavenging activities were highly enhanced compared to non-fermented blueberry puree after fermentation. Interestingly, the antioxidant activities were greatly increased in the fermentation of blueberry puree alone without supplements. The present results indicate that the blueberry puree fermented by Lactobacillus plantarum CK10 could be used as a potential source of natural antioxidants and these findings will facilitate the utilization of blueberry as a resource for food additive.

Keywords: antioxidant activity, blueberry, lactobacillus plantarum CK10, fermentation

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Anshu Radha Aggarwal

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As per the Right to Education Act (RTE), 2009, every child in the age group of 6-14 years shall be admitted in a neighborhood school. All the Out of School Children identified have to be enrolled / mainstreamed in to age appropriate class and there-after be provided special training. This paper addresses issues emerging from provisions in the RTE Act that specifically refer to the enrolment of out-of school children into age appropriate classes and the requirement to provide special trainings that will enable this to take place. In the context of RTE Act, the Out-of-School Children are first enrolled in the formal school and then they are provided with Special Training through NRSTCs (Long Term / Short term basis). These centers are functioning in formal school campus itself. This paper specifies the role of special training centers (STC). It presents a re-envisioning of assessment that recognizes two principal functions of assessment, assessment for learning and assessment of learning, instead of the more familiar categories of formative, diagnostic, summative, and evaluative assessment. The use of these two functions of assessment highlights and emphasizes the role of special training centers (STC) to assess their level for giving them appropriate special training and to evaluate their improvement in learning level. Challenge of problem faced by teachers to do diagnostic assessment, including its place in the sequence of assessment procedures appropriate in identifying and addressing individual children’s learning difficulties are solved by special training centers (STC). It is important that assessment is used to identify children with learning difficulties at the earliest possible stage so that appropriate support and intervention can be put in place. So appropriate challenges with tools are presented here for their assessment at entry level and at completion level of primary children by special training centers (STC).

Keywords: right to education, assessment, challenges, out of school children

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Authors: Nditsheni Ramakuela, Sonto Maputle, Base Khoza, Augustine Tugli

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Inadequate health literacy can cause difficulties in understanding and compliance to treatment plan. With diabetic condition, self-care activities include behaviours of following a diet plan, avoiding high fat foods, increased exercise, self-glucose monitoring, and foot care. Patients with poor health literacy have difficulty interpreting medication warning labels, following directions on a prescription label and identifying their medications. Difficulties in understanding and performing self-care and health-related activities may ultimately lead to poor health outcomes. The study explored and described factors affecting health literacy and self-care to diabetic regimen by female patients at selected hospital in Limpopo Province of South Africa. Qualitative and explorative research design was used. Female patients who were admitted and diagnosed with diabetes in female medical ward constituted the study population. Non-probability, purposive sampling was used to select 20 female patients diagnosed with diabetes, who were above 18 years and admitted during April–November 2014. An in-depth face-to-face, unstructured interview was used to collect data. Data were analysed using open coding method. Measures to ensure trustworthiness and ethical considerations were adhered to. Findings revealed factors affecting health literacy for diabetic self-care activities amongst patients were; patient, family, disease and facility related. Proposed recommendations were; to strengthen diabetes education and patient-provider partnership. This is important and must be transferred to strengthen self-care activities to fully benefit the patient.

Keywords: compliance, diabetes mellitus, diabetic regimen, health literacy, self activities

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Authors: Maria Lubomira Kubica

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The paper reveals the birth and evolution of the British precedent Rylands v. Fletcher that, once adopted on the other side of the Ocean (in United States), gave rise to a general clause of liability for abnormally dangerous activities recognized by the §20 of the American Restatements of the Law Third, Liability for Physical and Emotional Harm. The main goal of the paper was to analyze the development of the legal doctrine and of the case law posterior to the precedent together with the intent of the British judicature to leapfrog from the traditional rule contained in Rylands v. Fletcher to a general clause similar to that introduced in the United States and recently also on the European level. As it is well known, within the scope of tort law two different initiatives compete with the aim of harmonizing the European laws: European Group on Tort Law with its Principles of European Tort Law (hereinafter PETL) in which article 5:101 sets forth a general clause for strict liability for abnormally dangerous activities and Study Group on European Civil Code with its Common Frame of Reference (CFR) which promotes rather ad hoc model of listing out determined cases of strict liability. Very narrow application scope of the art. 5:101 PETL, restricted only to abnormally dangerous activities, stays in opposition to very broad spectrum of strict liability cases governed by the CFR. The former is a perfect example of a general clause that offers a minimum and basic standard, possibly acceptable also in those countries in which, like in the United Kingdom, this regime of liability is completely marginalized.

Keywords: abnormally dangerous activities, general clause, Rylands v. Fletcher, strict liability

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: A. Schuchter, M. Promegger

Abstract:

The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

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Authors: Jean Paul M. Milambo

Abstract:

Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

Procedia PDF Downloads 78