The new normal education requires learners to be independent in the learning process without face-to-face instruction. This study determined the home-based learning activities in relation to the academic achievement of Grade 6 learners in Plaridel North District, Municipality of Plaridel, Misamis Occidental. The descriptive-correlational design was used in the study. There were 135 students who served as respondents, selected through purposive and convenient sampling techniques. The researcher-made Home-Based Learning Activities Questionnaire was used as (...) a research instrument in determining the learners’ learning activities at home. Documentary analysis was made to determine the learners' academic achievement. Mean, Standard Deviation, Pearson Product-Moment Correlation Coefficient, and Regression Analysis were used as statistical tools in analyzing the data gathered. Results revealed that the respondents had a very high engagement in home-based learning activities, and their academic achievement was generally very satisfactory. The level of engagement in home-based learning activities was highly influential to the learners' academic achievement. The efforts extended for modular distance learning can determine what learners can achieve academically. (shrink)

Home-based biology experiments are activities that utilize household materials that have been adapted for the remote learning environment and are aligned to standard learning competencies. Recognizingthe households and kitchens as extensions of laboratories, HBEs can be used to deliver authentic learning experiences for the students at home. Furthermore, there are several attributes of HBEs that should be considered before the implementation of the activity. These attributes are, it is ethical and safe to perform, it (...) produces tangible products, encourages students to reflect, promotes collaboration, materials are easy-to-find and affordable and lastly, home-based biology experiments are modifiable. Also, HBE encourages students to work independently under the supervision of their parents and teachers. Parents and guardians, as collaborators, should ensure students'safety, monitor their child’s progress, provide a safe environment and conducive work area, and should report all cases of accidents and problems to the subject teacher. In conclusion, home-based biology experiments are one of the emerging teaching tools for remote authentic learning in the new normal. Moreover, HBEs could also be used to address the problem of the lack of hands-on activity in remote learning. Further studies should be conducted on the effectiveness of HBEs in different topics in biology. (shrink)

Face-to-face learning engagement has been suspended due to the health crisis that affected the whole world. This led to the adaptation of modular distance learning to continue delivering quality education. As the transition continues, its effectiveness has been frequently assessed. The key purpose of this study is to determine the relationship between the level of implementation of modular distance learning and English Writing Proficiency among the senior high school students in Saint Joseph College Maasin City School year (...) 2021-2022. The study employed a descriptive correlational design with 39 purposively chosen respondents. The main tools used in gathering the data were questionnaires, learning modules, and rubrics. Findings revealed that the implementation of modular distance learning (MDL) has an overall very satisfactory rating based on the perception of the students. The student’s perception of the implementation of modular distance learning and their writing proficiency is significantly related. Moreover, it revealed that students had difficulties in finding supplementary learning materials and educational support from home. The researcher recommends a set of guidelines for the successful and effective implementation of modular distance learning as the output of the study. (shrink)

A nation’s economy runs on the knowledge and skills of its people.Quality assurance mechanisms for higher education institutions must take cognizance of the graduates' acquisition of skills to become productive and contributory for societal development. The study is a quantitative survey assessing the attainment of the immediate program learning outcomes of the graduating Bachelor of Science in Information Technology of one campus of a public higher education institution in the Philippines. It also assessed the introspection and level of satisfaction (...) of the graduates in their studies. Findings disclosed that the graduates have a high level of attainment of the program's learning outcomes and a high level of satisfaction. The high school where the respondents graduated is the single variable that defined the difference in attainment of program intended learning outcomes. As to the graduates' introspections, themost significant percentage of them learned the program from family, relatives, and friends. Reasons for pursuing the degree program are because of parents’ influence, prestige of IT profession. Meanwhile, the university's reputation, affordable tuition fees, and proximity to home were the factors affecting the enrolment in the BSIT program. The findings will be the basis for strategic program interventions of the program. (shrink)

The Internet of Things (IoT) infrastructure forms a gigantic network of interconnected and interacting devices. This infrastructure involves a new generation of service delivery models, more advanced data management and policy schemes, sophisticated data analytics tools, and effective decision making applications. IoT technology brings automation to a new level wherein nodes can communicate and make autonomous decisions in the absence of human interventions. IoT enabled solutions generate and process enormous volumes of heterogeneous data exchanged among billions of nodes. This results (...) in Big Data congestion, data management, storage issues and various inefficiencies. Fog Computing aims at solving the issues with data management as it includes intelligent computational components and storage closer to the data sources. Often, an IoT-enabled infrastructure is shared among many users with various requirements. Sharing resources, sharing operational costs and collective decision making (consensus) among many stakeholders is frequently neglected. This research addresses an essential requirement for adaptive, autonomous and consensus-based Fog computational solutions which are able to support distributed and in-network schemes and policies. These network schemes and policies need to meet the requirements of many users. In this work, innovative consensus-based computational solutions are investigated. These proposed solutions aim to correlate and organise data for effective management and decision making in Fog. Instead of individual decision making, the algorithms aim to aggregate several decisions into a consensus decision representing a collective agreement, benefiting from the individuals variant knowledge and meeting multiple stakeholders requirements. In order to validate the proposed solutions, hybrid research methodology is involved that includes the design of a test-bed and the execution of several experiments. In order to investigate the effectiveness of the paradigm, three experiments were designed and validated. Real-life sensor data and synthetic statistical data was collected, processed and analysed. Bayesian Machine Learning models and Analytics were used to consolidate the design and evaluate the performance of the algorithms. In the Fog environment, the first scenario tests the Aggregation by Distribution algorithm. The solution contribute in achieving a notable efficiency of data delivery obtained with a minimal loss in precision. The second scenario validates the merits of the approach in predicting the activities of high mobility IoT applications. The third scenario tests the applications related to smart home IoT. All proposed Consensus algorithms use statistical analysis to support effective decision making in Fog and enable data aggregation for optimal storage, data transmission, processing and analytics. The final results of all experiments showed that all the implemented consensus approaches surpass the individual ones in different performance terms. Formal results also showed that the paradigm is a good fit in many IoT environments and can be suitable for different scenarios when applying data analysis to correlate data with the design. Finally, the design demonstrates that Fog Computing can compete with Cloud Computing in terms of accuracy with an added preference of locality. (shrink)

Aim: This study attempted to assess the organizational resiliency in the implementation of Basic Education School Learning Continuity Plan and to design a resilient basic education school learning continuity plan. -/- Methodology: The study used mixed method which is quantitative and qualitative. The data for the quantitative part of the study were gathered through a survey with the 19 school heads and 345 teacher- respondents while the qualitative method was conducted through focus group discussion interview with 19 key (...) informants who were composed of the teachers, school heads and stakeholders. The research instrument that was used for the perceived organizational resiliency was a survey questionnaire that was validated by the experts and which the reliability was tested through Cronbach’s alpha with excellent level of internal consistency. The statistical treatment for quantitative results used mean and standard deviation to determine the perception of the respondents with regards to the organizational resiliency on the implementation of the BE-SLCP and Pearson Product Moment Correlation Coefficient, testing its significance at the 0.05 level was used in finding out the relationship between the evaluation of the basic education school learning continuity plan and school performance indicators and organizational resiliency. While content analysis was employed for the qualitative results. -/- Results: The salient findings of the study were as follows: The result showed that the rate of enrollment during pandemic is low while the drop-out rate fostered a positive rate. The school heads and teacher respondents perceived the schools’ organizational resiliency as high. Based on the feedback of the key informants the lessons learned from the implementation of Basic Education School Learning Continuity Plan are strong collaboration, consistent communication, and enhanced ICT Skills. The best practices that were observed are sustained partnership and continuous implementation of programs, projects, and activities. The challenges encountered include authenticity of assessment and low capability of learning facilitators at home. The respondent assessed the developed learning continuity plan as very highly satisfactory. -/- Conclusion: The organizational resiliency of schools is high in its performance of continuing education during pandemic. The study suggests that the schools may developed creative strategies on increasing enrolment; the school may strengthen its school-based management level to ensure that the plans and goals for continuity of education will be achieved; the school may also consider strengthening the stakeholders’ involvement and the school may consider the strategy of close coordination and constant monitoring and follow-ups with parents/guardians on the implementation of learning delivery. (shrink)

The study investigated the awareness and utilization of e-learning technologies among vocational and technical education (VTE) students. A descriptive survey research design was used for this study, and the population consisted of 551 VTE students. A simple random sample of 62 VTE students was selected. The data collection instrument was a questionnaire. The reliability of the questionnaire was assessed using Cronbach's alpha analysis, and the reliability index was found to be within the acceptable limit of 0.70. An online survey (...) using Google Forms was used to collect the data. The study tested two null hypotheses using binary logistic regression models based on age, department level of study, and devices owned. The data was analyzed using frequency, percentages, and mean. The major findings from the data analysis indicated that VTE students had an awareness and utilization rate of 84.8% for the e-learning website, 75.6% for Google Classroom, and 60.6% for smart boards and video conferencing. However, 24.4% of the students were still unaware of the Moodle Learning Management System and the Canvas e-learning platform at the University of Nigeria Nsukka. Based on these findings, it is recommended that VTE students receive proper training to effectively utilize the e-learning technologies available to them, which would aid in fostering creativity and innovation. (shrink)

[This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a nutshell (...) explanation for student learning in general. I argue that identifying the person with the brain is scientism (not science), that the brain is not the person, and that it is the person who learns. In fact the brain only responds to the learning of embodied experience within the extra-neural network of intersubjective communications. Learning is a dynamic, cultural activity, not a neural program. Brain-based learning is unnecessary for educators and may be dangerous in that a culturally narrow ontology is taken for granted, thus restricting our creativity and imagination, and narrowing the human community. (shrink)

Adaptation and stress are two main concepts useful for better understanding the phases of illness and health-related human behavior. The two faces of adaptation, adaptation as a process and adaptation as a product, have raised the question of how long the adaptation process will take in cancer trajectories. The care setting transition from clinical-based into home-based cancer care has stressed the role of family caregivers (FCG) in cancer management. This study examines how types of demanded healthcare information (...) affect the FCG’s role in catalyzing the adaptation of female cancer patients. The mindsponge theory was used in conceptual development and results interpretation. Bayesian Mindsponge Framework (BMF) analytics was used for statistical analysis on a dataset of 48 spouses (husbands) and 12 other family members in five congested communities of Surabaya, Indonesia. Results showed that among the six types of demanded healthcare information, FCGs with a higher tendency to demand cancer-specific information are more likely to need support in catalyzing the adaptation of female cancer patients. Meanwhile, FCGs with a higher demand for information on alternative therapies are less likely to need support in catalyzing cancer adaptation. Other types of healthcare information have ambiguous effects on the need for support in cancer adaptation assistance. This study reveals that the demanded cancer-specific information, e.g., cancer’s prognosis or likely outcome, must be prioritized to assist FCG’s role in catalyzing adaptation among female cancer patients. Cancer prognosis and outcomes reflect the future of cancer care results. (shrink)

This study explores the effectiveness of brain-based learning (BBL) as a pedagogical approach to address the challenges of poor conceptual understanding, which may have worsened due to the COVID-19 pandemic aftermath. In this meta- analysis, 14 studies qualified using the Publish or Perish software and the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Statistical analysis conducted using Comprehensive Meta-Analysis (CMA) Version 4 software by Biostat, Inc. Based on the results, the overall effect size (ES = 3.135) (...) indicates that the use and integration of BBL principles and strategies have a significantly large and positive effect on student conceptual understanding. The moderator analysis revealed a significant difference between individual studies (p < .001); however, the overall results for academic level (p > .05) and discipline (p > .05) revealed no significant differences. Hence, each study included in this analysis may differ from one another due to the differences in various BBL strategies implemented; however, when grouped, they shared common effect sizes. With these findings, the researchers advocate the use of BBL principles and strategies to improve students' conceptual understanding at various levels in basic education, be it in English and STEM. Moreover, empirical studies focusing on a particular BBL variable, such as health and nutrition, are recommended for in-depth analysis and discussion. (shrink)

Preparing students for the real challenges in life is one of the most important goals in education. Constructivism is an approach that uses real-life experiences to construct knowledge. Problem-Based Learning (PBL), for almost five decades now, has been the most innovative constructivist pedagogy used worldwide. However, with the rising popularity, there is a need to revisit empirical studies regarding PBL to serve as a guide and basis for designing new studies, making institutional policies, and evaluating educational curricula. This (...) need has led the researchers to do a meta-analysis to analyse the effectiveness of PBL on secondary students’ achievement in different scientific disciplines. Following the set of inclusion and exclusion criteria, 11 studies in Eurasia, Africa, and America conducted from 2016 to 2020 have qualified for this study. Six of which focused on JHS (n = 1047) and five on SHS (n = 375). Studies were obtained from various meta-search engines including Google, ERIC, and JSTOR. Further, the researchers used Harzing’s Publish and Perish software to exhaust the search process. Sample size, mean, and standard deviation were analysed using the Comprehensive MetaAnalysis version 3 to determine the effect sizes (Hedge’s g) and the results of moderator analysis, forest plot, funnel plot, and Begg-Mazumdar test. Findings have shown that PBL, as an approach to teaching science, had a large and positive effect (ES = .871) on the achievement of secondary students. However, grade levels and various scientific disciplines did not influence students’ learning achievement. The conduct of more studies on the different factors affecting PBL implementation and specific effects of PBL on various student domains is recommended to facilitate comparative educational research in the future. (shrink)

Team-based learning (TBL) was applied within a third-year unit of study about ethics and management with the aim of enhancing students’ teamwork skills. A survey used to collect students’ opinions about their experience with TBL provided insights about how TBL helped students to develop an appreciation for teamwork and team collaboration. The team skills acquired through TBL could strengthen job readiness for business.

In this essay I argue that theorists such as Kohn and Mitra have been too hasty in pronouncing the superiority of problem-based learning over direct instruction.

Problem-Based Learning has become an increasingly popular instructional method for a variety of disciplines at all levels. Many studies and meta-analyses of these studies have shown the efficacy of this method for developing knowledge and skills. I adopted this method for teaching Engineering Ethics at Carnegie Mellon University, which has as its main course objectives the development of moral reasoning skills, as well as collaboration and communication skills, with special attention given to ethical dilemmas that may arise in (...) the normal course of an engineer’s professional career. In the most recent iteration of the course, I used the Engineering and Science Issues Test as a pretest and posttest to test the development of my students’ moral reasoning skills over the course of the semester. Based on the results of these tests, I argue that the students in my Engineering Ethics course did in fact significantly develop their moral reasoning skills. (shrink)

Problem-Based Learning has become an increasingly popular instructional method for a variety of disciplines at all levels. Many studies and meta-analyses of these studies have shown the efficacy of this method for developing knowledge and skills. I adopted this method for teaching Engineering Ethics at Carnegie Mellon University, which has as its main course objectives the development of moral reasoning skills, as well as collaboration and communication skills, with special attention given to ethical dilemmas that may arise in (...) the normal course of an engineer’s professional career. In the most recent iteration of the course, I used the Engineering and Science Issues Test as a pretest and posttest to test the development of my students’ moral reasoning skills over the course of the semester. Based on the results of these tests, I argue that the students in my Engineering Ethics course did in fact significantly develop their moral reasoning skills. (shrink)

In this monograph we contrast two prominent models of education, Competence-Based Education (CBE), more recent and currently dominant in most school systems of the world, and Bildung-Oriented Education (BOE), once the basis of school systems of Northern Europe. CBE interprets learning as the acquisition of clearly definable and allegedly measurable competences, and is supported by supranational organisations, such as the OECD, which approach education from the perspective of the human capital theory. BOE instead characterises learning holistically as (...) aimed at the progressive articulation of a meaningful ‘big picture’ in the student’s mind. Emerged in Northern Europe under the influence of the ideals of the Enlightenment and Neo-Humanism of individual and collective autonomy and responsibility, BOE was subsequently enriched with a hermeneutical approach to teaching and socio-political objectives of emancipation and solidarity originating within Critical Theory. We argue that, in spite of its celebrated ‘scientificity’, CBE is internally incoherent and unreliable, contributes to structural forms of oppression and injustice, fosters social pathologies, and fails to provide students with the kind of intellectual autonomy they need as both human beings and citizens of our complex post-industrial societies. We also defend BOE from objections made by critical theorists, poststructuralists and postcolonial thinkers, and argue that it is a coherent and flexible model of education that endows students with autonomy and responsibility, and can help heal social pathologies. (shrink)

What is the primary function of consciousness in the nervous system? The answer to this question remains enigmatic, not so much because of a lack of relevant data, but because of the lack of a conceptual framework with which to interpret the data. To this end, we have developed Passive Frame Theory, an internally coherent framework that, from an action-based perspective, synthesizes empirically supported hypotheses from diverse fields of investigation. The theory proposes that the primary function of consciousness is (...) well-circumscribed, serving the 'somatic nervous system[. For this system, consciousness serves as a frame that constrains and directs skeletal muscle output, thereby yielding adaptive behavior. The mechanism by which consciousness achieves this is more counterintuitive, passive, and “low level” than the kinds of functions that theorists have previously attributed to consciousness. Passive frame theory begins to illuminate (a) what consciousness contributes to nervous function, (b) how consciousness achieves this function, and (c) the neuroanatomical substrates of conscious processes. Our untraditional, action-based perspective focuses on olfaction instead of on vision and is 'descriptive' (describing the products of nature as they evolved to be) rather than 'normative' (construing processes in terms of how they should function). Passive frame theory begins to isolate the neuroanatomical, cognitive-mechanistic, and representational (e.g., conscious contents) processes associated with consciousness. (shrink)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to (...) enhance model generalizability. (shrink)

The study has been presented the role of home environment to learn English language particularly in Bangladesh. Parental as well as siblings role is very essential to grow the sense of learning and the learners can grow a great influence by it. Parents’ as well as siblings’ positive attitude, education and awareness according to individual requirements and needs are provided constant encouragement and support for the learners. Parents make the greatest difference to achievement through supporting their learning (...) at home rather than supporting activities in school. A learner, whose family members are habituated to use English at home, feels encouraged to learn English which facilitates learning process. My findings, on the other hand, show that children of those parents who are ignorant of providing sound family atmosphere, lack confidence as well as self-esteem. This study also inspects the impact of home environment on children’s achievement in English language. The findings reveal that there is a constant relationship between the role of family and students’ academic achievement. (shrink)

This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over (...) the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness. (shrink)

This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over (...) the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness. (shrink)

The ever-evolving ways attacker continues to improve their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack. Thus, current anti-phishing methods remain vulnerable to complex phishing because of the increasingly sophistication tactics adopted by attacker coupled with the rate at which new tactics are being developed to evade detection. In this research, we proposed an adaptable (...) framework that combines Deep learning and Randon Forest to read images, synthesize speech from deep-fake videos, and natural language processing at various predictions layered to significantly increase the performance of machine learning models for phishing attack detection. (shrink)

This study aims to (1) describe the application of the roundtable cooperative model on narrative text teaching materials, (2) describe students’ responses to the application of the roundtable cooperative model on narrative text teaching materials, (3) describe the increase in students’ knowledge of narrative text teaching materials. The type of research used was classroom action research. Data collection techniques were observation, interviews, questionnaires, tests, and documentation. The data in this study were in the form of application, response, and increase in (...) students’ knowledge of implementing the roundtable cooperative model on narrative text teaching materials. Data were analyzed using interactive techniques, including data reduction, presentation, and concluding. The data validation technique used data and method triangulation. The study results show that (1) applying the roundtable cooperative model to narrative text teaching materials can improve students’ understanding and writing skills. These improvements include structure, storyline or sequence of events, writing development, and completeness of information according to the theme; (2) students’ responses to the application of the roundtable cooperative model show that 90.3% agree to use the cooperative model in narrative text teaching materials and 9.7% do not agree; (3) there is an increase in student learning outcomes. Before applying the roundtable cooperative model, the students get an average score of 56, and after applying it, they get an average score of 69. The results show that the roundtable cooperative model can be used in the learning process by using media that supports the roundtable cooperative model and teaching materials. (shrink)

Home management and controlling have seen a great introduction to network that enabled digital technology, especially in recent decades. For the purpose of home automation, this technique offers an exciting capability to enhance the connectivity of equipment within the home. Also, with the rapid expansion of the Internet, there are potentials that added to the remote control and monitoring of such network-enabled devices. In this paper, we had been designed and implemented a fully manageable and secure smart (...) home automation system based on a cloud computing system with an ESP Arduino system. The security of home had been improved by adding a complete camera system with a GSM communication technique to connect the Arduino output data to an external specified number if there is no internet provider. We used three sensors for temperature, gas, and motion measurements. The ESP8226 Wi-Fi device programmed the sensors to maintain the sensors measurements and transfer them to the cloud server database which is programmed to the web server via Appatshy and Mysql formats. The system implemented with high time response so that all readings updated and appeared spontaneously. The designed system should be effective, a secure, and rapid response real-time smart home system should be achieved. (shrink)

This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over (...) the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness. (shrink)

The emergence of the need for orientation since the past times led the universities to invent innovative ways to prepare their students for the activities and courses they will face. Hence, various types of orientation have been provided during history. However, today with the outbreak of the Covid-19 and the closure of the schools, most of the students are continuing their studies as distance learning. While this situation is very disappointing for all freshmen students who do not know the (...) university's atmosphere, it is extremely disruptive, specifically for the design ones, which are passing tactile courses, demanding being held face to face. This ascertains the research's problem as a need for an interactive solution for the issue to lessen the consequent problems. Game-based orientation (GBO) is a tool, engaging the freshmen students as players with the provided data in it, which are the essentials for a novel student to know before entering the university. It allows the student to be dealt with the school services, Istanbul Technical University in this case, and use them in terms of the game's tasks. The scoring system, the ultimate certificate, the leaderboard leading them to prizes, and the game's non-linearity will attract the students to use GBO frequently to finish it and experience all the possible scenarios. (shrink)

The involvement of parents in their children’s education affects the quality of their learning. The purpose of this study was to investigate the involvement of parents in the education of primary school children. The quantitative descriptive research method was employed to conduct the study. The population of the study was 3,297 children studying at the primary school level and their parents. A proportionate stratified random sampling technique was used to select 348 students and their parents for data collection. The (...) data were collected from children and their parents through a five-point scale. The research instrument consisted of six factors: parenting, communicating, decision-making, learning at home, volunteering, and collaboration with the community. The data were collected through personal visits by the researchers. Data were analyzed through mean, standard deviation, Kruskal Wallis, and Mann-Whitney U test. The research study concluded that primary school students and their parents hold the same perspective regarding parental involvement in their children's education. However, there was a significant difference in parental involvement in their children’s education, as the students reported, based on their demographic characteristics and the educational institutions they were attending. It is suggested to adapt the involvement of parents according to the needs of students of different age groups and grades by developing a strong and continuous connection between school and home. (shrink)

The current increase of air pollution rates and its consequences of global warming, health problems and threats to human lives necessitate the continuous search for more efficient and cost effective gas monitoring devices. Devices that is easily available and implementable worldwide. In developing countries the cost and the availability of the equipment is one of the obstacles that contribute to not having an efficient monitoring system. Hence, modifying cheap and easily available devices to work as pollution monitoring system will be (...) an asset in this direction. In this work I am presenting the design of a computer based pollution detection and measuring system using cheap CO (Carbon Monoxide) alarms used in homes. The outcome is a cost-effective computer based CO monitoring system that is easily available and could be easily modified to work as a network based CO nose. A C# based program is also designed to show and log the sensor readings in an easy to use and read Window. (shrink)

Due to the unprecedented COVID-19 incident, basic education institutions have faced different challenges in their teaching-learning activities. Particularly conducting assessments remotely during COVID-19 has posed extraordinary challenges for basic education institutions owing to lack of preparation superimposed with the inherent problems of remote assessment. Descriptive-evaluation research was employed since the present study attempts to examines the assessment practices and competences on remote learning assessment of teachers in Graceville National High School. For the study, questionnaires were prepared and data (...) nine (9) senior high school teachers and forty-two (42) junior high school teachers were collected and analyzed. The gathered data from this study were subjected to the descriptive and inferential statistics. The data revealed that the most frequent number of the teacher- respondents in the study was 36 - 40 years old at age, female, Technology Livelihood Education (TLE) major, 6 - 10 years in service in Department of Education, and bachelor's degree holders. More so, the teacher respondents' level of teacher competencies on remote learning assessment was observed high competent. In addition, level of assessment practices in terms of clarity of assessment, time and effort on task, quality of feedback, motivational belief and self-esteem to learners, self-assessment and reflection of learning of the learners, and assessment - content and process in adapting teaching to students needs was mostly practice. However, it was completely practicing the interaction and dialogue about learning progress. The results confirmed that there was a significant difference on the teacher respondents' level of competence on the remote learning assessment when group according to their age, gender, areas of specialization, and training attended. On the other hands, teacher year of teaching and educational attainment revealed it has no significant difference on their level of competence on the remote learning assessment. Looking forward, that age, gender, year of teaching, areas of specialization, educational attainment, and training attended significantly differs to the level of assessment practices of the teachers. It also observed that the teachers experiencing highly challenges encountered on the remote learning assessment. It is recommended to implement the proposed school-based testing reforms and should be monitored and evaluated for the optimum advantage of the school and community. (shrink)

: COVID-19 has proliferated over the earth, exposing mankind at risk. The assets of the world's most powerful economies are at stake due to the disease's high infectivity and contagiousness. The capacity of machine learning algorithms can estimate the amount of future COVID-19 cases, which is now considered a possible threat to civilization. Five conventional measuring models, notably LR, LASSO, SVM, ES, and LSTM, were utilised in this work to examine COVID-19's undermining variables. Each model contains three sorts of (...) expectations: the number of newly contaminated cases, the number of passings, and the number of recoveries. However, it is hard to anticipate the patients' real outcomes. To address the issue, a suggested approach based on long transient memory (LSTM) forecasts the number of COVID-19 cases in the next 10 days as well as the impact of preventative measures such as social isolation and lockdown on COVID-19 spread. (shrink)

In modern days, person-computer communication systems have gradually penetrated our lives. One of the crucial technologies in person-computer communication systems, Speech Emotion Recognition (SER) technology, permits machines to correctly recognize emotions and greater understand users' intent and human-computer interlinkage. The main objective of the SER is to improve the human-machine interface. It is also used to observe a person's psychological condition by lie detectors. Automatic Speech Emotion Recognition(SER) is vital in the person-computer interface, but SER has challenges for accurate recognition. (...) In this work to resolve the above problem, automatic Speech enhancement shows that deep learning techniques effectively eliminate background noise. Using Deep leaning models for four states were created: happy, sad, angry, and intoxicated. Recurrent Neural Network (RNN) algorithm used to reduce the possibility of over fitting by randomly omitting neurons in the hidden layers. The proposed RNN method could be implemented in personal assistant systems to give better and more appropriate state-based interactions between humans. In the simulation results shows Improving accuracy, Time complexity, Error rate is also reduced to using the proposed method. -/- . (shrink)

This study was conducted to explore the effects of cloud-based m- learning on students’ motivation and creative performance in computer illustration course. Variables of motivation, creative behavior, creative process and creative product were conducted to understand the situations, differences, and the predictive power cloud-based m-learning had in creative performance. A nonequivalent pretest–posttest design was adopted, and 123 university students from Taipei City, Taiwan,were recruited as research participants in the study during 10-weeks experiment. They were asked to (...) complete a motivation questionnaire. Creative concept form and students’ illustraion work were also collected for statistics analysing. Through the descriptive statistics, one-way ANCOVA, and multiple linear regression analysis, the findings are as follows: (1)cloud-based m- learning had a positive effect on students’ motivation in computer illustration course; (2) cloud-based m-learning had a positive effect on creative performance in computer illustration course; (3) students with higher motivation performed better on creative performance, and(4) motivation could partially mediate cloud-based m-learning and creative performance. (shrink)

With the current improvement of development towards pharmaceutical, distinctive ultrasound methodologies are open to find the fetal prosperity. It is analyzed with diverse clinical parameters with 2-D imaging and other test. In any case, prosperity desire of fetal heart still remains an open issue due to unconstrained works out of the hatchling, the minor heart appraise and inadequate of data in fetal echocardiography. The machine learning strategies can find out the classes of fetal heart rate which can beutilized for (...) earlier evaluating. With this background, we have utilized Cardiotocographic Fetal heart rate dataset removed from UCI Machine Learning Store for predicting the fetal heart rate health classes. The Prediction of fetal health rate are achieved in six ways. Firstly, the data set is preprocessed with Feature Scaling and missing values. Secondly, exploratory data investigation is done and the dispersion of target feature is visualized. Thirdly, the raw data set is fitted to all the classifiers and the performance is analysed before and after feature scaling. Fourth, the raw data set is subjected to undersampling methods like ClusterCentroids, RepeatedENN, AllKNN, CondensedNearestNeighbour, EditedNearestNeighbours, InstanceHardnessThreshold and NearMiss. Fifth, the undersampled dataset by above mentioned methods are fitted to all the classifiers and the performance is analyzed before and after feature scaling. Sixth, performance analysis is done using metrics like Precision, Recall, F-score, Accuracy and running time. The execution is done using python language under Spyder platform with Anaconda Navigator. Experimental results shows that the Decision Tree classifier tends to retain 98% before and after feature scaling for the underrsampling with EditedNearestNeighbours, RepeatedENN and AllKNN methods. (shrink)

Due to the COVID-19 outbreak, education was interrupted. To continue offering high-quality education led to a dramatic transition away from face-to-face instruction and to blended learning. However, modular distance learning, as one of the adaptable learning modes, was chosen by most parents. Hence, this study seeks to determine the role of parents in the effectiveness of modular distance learning during the COVID-19 pandemic era, ascertain whether there is a relationship between the parents’ roles and their backgrounds, (...) determine whether there is a relationship between the parents’ backgrounds and the children’s academic performance and determine whether the child’s educational performance was related to the role of the parents. A survey questionnaire was used to acquire information on the parents’ profiles and the role they played or did not play. Mean, frequency count, and Spearman correlation were used to analyze the data. Results showed a relationship between parents’ profiles and roles in their child’s academic achievement. The children’s academic performance in modular distance learning is boosted, mainly if the parents work and earn a higher income. Modular distance learning is effective when parents act as friendly teachers and motivators for their children and are employed in either public or private agencies. -/- . (shrink)

We discuss the evolutionary transition from animals with limited experiencing to animals with unlimited experiencing and basic consciousness. This transition was, we suggest, intimately linked with the evolution of associative learning and with flexible reward systems based on, and modifiable by, learning. During associative learning, new pathways relating stimuli and effects are formed within a highly integrated and continuously active nervous system. We argue that the memory traces left by such new stimulus-effect relations form dynamic, flexible, (...) and varied global sensory states, which we call categorizing sensory states . These CSSs acquired a function: they came to act as internal “evaluators” and led to positive and negative reinforcement of new behavior. They are therefore the simplest, distinct, first-person motivational states that an animal can have. They constitute what we call basic consciousness, and are the hallmark of animals that can experience. Since associative learning has been found in many invertebrate taxa that first appeared during the Cambrian era, we propose that the processes underlying basic consciousness are phylogenetically ancient, and that their emergence may have fueled the Cambrian explosion. (shrink)

The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...) way things appear to us. The second candidate for cognitive penetration is Fiona Macpherson’s claim that, in addition to concepts, our beliefs can penetrate perceptual experiences. It is argued that neither candidate is a case of cognitive penetration. In doing so, I provide an explanation to both that is based on perceptual learning, a non-cognitive phenomenon where relatively slow and long-lasting modifications to an organism’s perceptual system bring about changes in perception. This explanation is theoretically more plausible and remains closer to the empirical data than the explanations based on cognitive penetration. (shrink)

COVID-19 and military actions on the territory of Ukraine fundamentally changed the organization of the educational process, forcing educational institutions to transfer classroom learning to virtual space. To organize the educational process remotely, we need to organize an educational environment in which we can ensure the implementation of all types of educational activities, as well as creation and selection of e-resources depending on their types. Having guidelines in the form of modes, forms and learning outcomes, it is necessary (...) to structure the content of educational disciplines, corresponding curricula, to ensure the activity of students during lectures and the implementation of practical tasks with the necessary tools, to determine and carry out the selection of electronic educational resources for the effective organization of the educational process in conditions of open education. First of all, it is important to take into account all types of student activities, namely: those ones, which are usually implemented in class and determine the possibility of their implementation in a remote format using cloud services. The monograph considers the problem of effective use of Microsoft 365 services for the organization of e-learning through the prism of the competency approach. In particular, the study established a correspondence between training activities and M365 services, which can provide tools support for their implementation. Chapter 1 analyzes the components of digital competence and the abilities necessary for the organization of the e-learning process. Based on the analysis, the correspondence between the components of digital competence and M365 services, the possession of which indicates the existing level of digital competence, was established. Chapter 2 of the monograph describes the digital competences necessary for the organization of various types of training using Microsoft 365 services. It studies features of using digital identity cloud services, Microsoft 365 services for digital data management and collaboration, e-learning management, design and creation of digital content, problem solving and innovation, digital communication, cooperation and interaction. Chapter 3 offers a developed model of hybrid educational environment architecture based on Microsoft Teams platform and analyzes digital competences for the organization of asynchronous interaction between students and teachers using MS Teams tools. Chapter 4 is devoted to the results of an experimental study of the effectiveness of the use of Microsoft 365 services for the organization of e-learning and the readiness of teachers and students to use them. (shrink)

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring (...) that the resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

The Internet of Things (IoT) is a rapidly growing technology that connects and integrates billions of smart devices, generating vast volumes of data and impacting various aspects of daily life and industrial systems. However, the inherent characteristics of IoT devices, including limited battery life, universal connectivity, resource-constrained design, and mobility, make them highly vulnerable to cybersecurity attacks, which are increasing at an alarming rate. As a result, IoT security and privacy have gained significant research attention, with a particular focus on (...) developing anomaly detection systems. In recent years, machine learning (ML) has made remarkable progress, evolving from a lab novelty to a powerful tool in critical applications. ML has been proposed as a promising solution for addressing IoT security and privacy challenges. In this article, we conducted a study of the existing security and privacy challenges in the IoT environment. Subsequently, we present the latest ML-based models and solutions to address these challenges, summarizing them in a table that highlights the key parameters of each proposed model. Additionally, we thoroughly studied available datasets related to IoT technology. Through this article, readers will gain a detailed understanding of IoT architecture, security attacks, and countermeasures using ML techniques, utilizing available datasets. We also discuss future research directions for ML-based IoT security and privacy. Our aim is to provide valuable insights into the current state of research in this field and contribute to the advancement of IoT security and privacy. (shrink)

The mental risk poses a high threat to the individuals, especially overseas demographic, including expatriates in comparison to the general Arab demographic. Since Arab countries are renowned for their multicultural environment with half of the population of students and faculties being international, this paper focuses on a comprehensive analysis of mental health problems such as depression, stress, anxiety, isolation, and other unfortunate conditions. The dataset is developed from a web-based survey. The detailed exploratory data analysis is conducted on the (...) dataset collected from Arab countries to study an individual’s mental health and indicative help-seeking pointers based on their responses to specific pre-defined questions in a multicultural society. The proposed model validates the claims mathematically and uses different machine learning classifiers to identify individuals who are either currently or previously diagnosed with depression or demonstrate unintentional “save our souls” (SOS) behaviors for an early prediction to prevent risks of danger in life going forward. The accuracy is measured by comparing with the classifiers using several visualization tools. This analysis provides the claims and authentic sources for further research in the multicultural public medical sector and decision-making rules by the government. (shrink)

In the recent years, problem-solving become a central topic that discussed by educators or researchers in mathematics education. it’s not only as the ability or as a method of teaching. but also, it is a little in reviewing about the components of the support to succeed in problem-solving, such as student's belief and attitude towards mathematics, algebraic thinking skills, resources and teaching materials. In this paper, examines the algebraic thinking skills as a foundation for problem-solving, and learning cycle as (...) a breath of continuous learning. In this paper, learning cycle to be used is a modified type of 5E based on beliefs. (shrink)

The abrupt shift in learning mode demands students to adjust from the comfort of their homes, as well as the challenges of face-to-face learning. As a result, as the pandemic fades, institutions in the Philippines have begun to reopen their doors to students. Hence, this study employed a correlational design to investigate the relationship between procrastination and academic burnout among 150 first-year college students in a state university. Based on the statistical analysis, the r coefficient of 0.67 (...) indicates a moderate positive correlation between the variables. The p-value of 0.00, which is less than 0.05, leads to the decision to reject the null hypothesis. Hence, a significant relationship exists between procrastination and academic burnout among first-year college students. Implications and recommendations were discussed in the study. (shrink)

While representation learning techniques have shown great promise in application to a number of different NLP tasks, they have had little impact on the problem of ontology matching. Unlike past work that has focused on feature engineering, we present a novel representation learning approach that is tailored to the ontology matching task. Our approach is based on embedding ontological terms in a high-dimensional Euclidean space. This embedding is derived on the basis of a novel phrase retrofitting strategy (...) through which semantic similarity information becomes inscribed onto fields of pre-trained word vectors. The resulting framework also incorporates a novel outlier detection mechanism based on a denoising autoencoder that is shown to improve performance. An ontology matching system derived using the proposed framework achieved an F-score of 94% on an alignment scenario involving the Adult Mouse Anatomical Dictionary and the Foundational Model of Anatomy ontology (FMA) as targets. This compares favorably with the best performing systems on the Ontology Alignment Evaluation Initiative anatomy challenge. We performed additional experiments on aligning FMA to NCI Thesaurus and to SNOMED CT based on a reference alignment extracted from the UMLS Metathesaurus. Our system obtained overall F-scores of 93.2% and 89.2% for these experiments, thus achieving state-of-the-art results. (shrink)

Prediction-based decisions, which are often made by utilizing the tools of machine learning, influence nearly all facets of modern life. Ethical concerns about this widespread practice have given rise to the field of fair machine learning and a number of fairness measures, mathematically precise definitions of fairness that purport to determine whether a given prediction-based decision system is fair. Following Reuben Binns (2017), we take ‘fairness’ in this context to be a placeholder for a variety of (...) normative egalitarian considerations. We explore a few fairness measures to suss out their egalitarian roots and evaluate them, both as formalizations of egalitarian ideas and as assertions of what fairness demands of predictive systems. We pay special attention to a recent and popular fairness measure, counterfactual fairness, which holds that a prediction about an individual is fair if it is the same in the actual world and any counterfactual world where the individual belongs to a different demographic group (cf. Kusner et al. (2018)). (shrink)

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...) how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a (...) knowing community. And another part of this thinking is centered around the new, and the newly empowered, learner, the member of the net generation, who is thinking and interacting in new ways. These trends combine to form what is sometimes called 'e-learning 2.0' - an approach to learning that is based on conversation and interaction, on sharing, creation and participation, on learning not as a separate activity, but rather, as embedded in meaningful activities such as games or workflows. (shrink)

Due to the emergence of ICT in ELT sector, seasoned English teachers find it resistant to such a shift despite having a positive attitude towards its use. This quasi-experimental study aimed to examine the extent to which seasoned English language teachers developed their ICT skills through a Service-Learning Activity (SLA). Using a one-group pre- and post-test design, this study collected the data through a modified Needs Assessment Survey (NAS) distributed to fourteen purposively selected participants. It was administered to examine (...) what professional ICT development would greatly benefit them. The data were analyzed using descriptive statistics and themes according to the Service-Learning Activity (SLA) topics. A Post Evaluation Survey (PES) was administered, and its result was compared to the initial test. The results showed that the seasoned teachers gained significant learning gains in terms of (1) sharing of knowledge from other teachers; (2) being encouraged to use ICT tools; (3) training opportunities; (4) working with other colleagues; and 5) attending professional workshops which include SLA. However, this study unveiled that the English teachers had no significant difference in perceptions regarding the roles of computers in teaching before and after the intervention. Limitations and recommendations for future studies were discussed. (shrink)

Underlying much current work in philosophy of imagination is the assumption that imagination is a skill. This assumption seems to entail not only that facility with imagining will vary from one person to another, but also that people can improve their own imaginative capacities and learn to be better imaginers. This paper takes up this issue. After showing why this is properly understood as a philosophical question, I discuss what it means to say that one imagining is better than another (...) and then discuss the kinds of imagination training and techniques that might be employed in an effort to get better at imagining. The discussion of these techniques draws insight from consideration of other skills-based activities, as well as from consideration of the creation of art and our engagement with literature and poetry. Over the course of this discussion, we also gain further insight into the nature of imagination. (shrink)

Effective ethics teaching and training must cultivate both the critical thinking skills and the character traits needed to deliberate effectively about ethical issues in personal and professional life. After highlighting some cognitive and motivational obstacles that stand in the way of this task, the article draws on educational research and the author's experience to demonstrate how cooperative learning techniques can be used to overcome them.