Search results for: self-regulated learning theory

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: Elizabeth McLean, Katrina Skewes-McFerran, Grace Thompson

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Scholarship highlights the need to further examine and better understand and foster the process of becoming a parent to a premature baby in the neonatal context to support the critical development of the parent-infant relationship. Music therapy research documents significant benefits of music therapy on neonatal physiological and neurodevelopmental function, reduced maternal anxiety and validating parents’ relationship with their premature baby, yet limited studies examine the role of music in supporting parental identity. This was a multi-site study, exploring parents’ musical engagement with their hospitalised baby and parental identity in a NU. In-depth interviews with nine parents of a premature baby across varying time points in their NU journey took place. Data collection and analysis was influenced by Constructive Grounded Theory methodology. Findings in the form of a substantive grounded theory illuminated the contribution of parents’ musical engagement on their sense of parental identity in the NU. Specifically, the significance of their baby’s level and type of response during musical interactions in influencing parents’ capacity to engage in musical dialogue with their baby emerged. Specific conditions that acted as both barriers and fosters in parents’ musical engagement across a high- risk pregnancy and NU admission also emerged. Recommendations for future research into the role of music and music therapy in supporting parental coping and transition to parenthood during a high-risk pregnancy and birth and beyond the NU will be discussed.

Keywords: grounded theory, musical engagement, music therapy, parental identity

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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: Abdullah Abu-Tineh, Youmen Chaaban

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This study examines the development of a professional development (PD) model for teacher growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge and skills of both school leadership and teachers in an attempt to improve student learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents findings from an evaluation of this PD program. Based on an adaptation of Guskey’s evaluation of PD models, 100 teachers at the participating schools were selected for classroom observations and 40 took part in in-depth interviews to examine changed classroom practices. The impact of the PD program on student learning was also examined. Teachers’ practices and their students’ achievement in English, Arabic, mathematics and science were measured at the beginning and at the end of the intervention.

Keywords: initiative, professional development, school based support Program (SBSP), school reform

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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: Sinchai Poolklai

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The purpose of this research paper was aimed to examine the level of satisfaction of the faculty members who participated in the ASEAN camp, Chantaburi, Thailand. The population of this study included all the faculty members of Suan Sunandha Rajabhat University who participated in the training and activities of the ASEAN camp during March, 2014. Among a total of 200 faculty members who answered the questionnaire, the data was complied by using SPSS program. Percentage, mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of satisfaction was 4.37, and standard deviation was 0.7810. Moreover, the mean average can be used to rank the level of satisfaction from each of the following factors: lower cost, less time consuming, faster delivery, more effective learning, and lower environment impact.

Keywords: ASEAN camp, e-learning, satisfaction, application

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Authors: Farouk Metiri, Halim Zeghdoudi, Mohamed Riad Remita

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Credibility theory is an experience rating technique in actuarial science which can be seen as one of quantitative tools that allows the insurers to perform experience rating, that is, to adjust future premiums based on past experiences. It is used usually in automobile insurance, worker's compensation premium, and IBNR (incurred but not reported claims to the insurer) where credibility theory can be used to estimate the claim size amount. In this study, we focused on a popular tool in credibility theory which is the Bayesian premium estimator, considering Lindley distribution as a claim distribution. We derive this estimator under entropy loss which is asymmetric and squared error loss which is a symmetric loss function with informative and non-informative priors. In a purely Bayesian setting, the prior distribution represents the insurer’s prior belief about the insured’s risk level after collection of the insured’s data at the end of the period. However, the explicit form of the Bayesian premium in the case when the prior is not a member of the exponential family could be quite difficult to obtain as it involves a number of integrations which are not analytically solvable. The paper finds a solution to this problem by deriving this estimator using numerical approximation (Lindley approximation) which is one of the suitable approximation methods for solving such problems, it approaches the ratio of the integrals as a whole and produces a single numerical result. Simulation study using Monte Carlo method is then performed to evaluate this estimator and mean squared error technique is made to compare the Bayesian premium estimator under the above loss functions.

Keywords: bayesian estimator, credibility theory, entropy loss, monte carlo simulation

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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: Dinesh N. Kurup, Celine Perriera

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The economic development of any country is based on the policies adopted by the government from time to time. If these policies are framed by the opinion of the people of the country, there is need for having strong knowledge base, right from the school level. There should be emphasis to provide in education, an ability to take informed decisions regarding socio-scientific issues. It would be better to adopt this practice in high school classrooms to build capacity among future citizens. This study is an attempt to provide a different approach of teaching and learning in classrooms at the high school level in Indian schools for providing opportunity for informed decision making regarding nuclear power use. A unit of work based on the 5E instructional model about the use of nuclear energy is used to build knowledge base and find out the effectiveness in terms of its influence for taking decisions as a future citizen. A sample of 120 students from three high schools using different curricula and teaching and learning methods were chosen for this study. This research used a design based research method. A pre and post questionnaire based on the theory of reasoned action, structured observations, focus group interviews and opportunity for decision making were used during the intervention. The data analysed qualitatively and quantitatively, and the qualitative data were coded into categories based on responses. The results of the study show that students were able to make informed decisions and could give reasons for their decisions. They were enthusiastic in formulating policy making based on their knowledge base and have strong held views and reasoning for their choice.

Keywords: informed decision making, socio-scientific issues, nuclear energy use, policy making

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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: Naoki Ohshima, Ken Kaminishi

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Four types of dependencies, which are 'Finish-to-start', 'Finish-to-finish', 'Start-to-start' and 'Start-to-finish (S-F)' as logical relationship are modeled based on the definition by 'the predecessor activity is defined as an activity to come before a dependent activity in a schedule' in PMBOK. However, it is found a self-contradiction in the precedence diagram for S-F relationship by PMBOK. In this paper, author would like to validate logical relationship of S-F by Graph Theory and propose a new interpretation of the precedence diagram for S-F relationship.

Keywords: project time management, sequence activity, start-to-finish relationship, precedence diagram, PMBOK

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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: Michael Oppong, Stephanie Owusu Ansah, Daniel Ofori

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The study investigated students’ post-covid-19 experiences with e-learning platforms among undergraduate students of public universities in the Ashanti region of Ghana. The study respectively drew 289 respondents from two public universities, i.e., Kwame Nkrumah University of Science and Technology (KNUST) Business School and the Kumasi Technical University (KsTU) Business School in Ghana. Given that the population from the two public universities was fairly high, sampling had to be done. The overall population of the study was 480 students randomly sampled from the two public universities using the sampling ratio given by Alreck and Settle (2004). The population constituted 360 students from the Kwame Nkrumah University of Science and Technology (KNUST) Business School and 120 from the Kumasi Technical University Business School (KsTU). The study employed questionnaires as a data collection tool. The data gathered were 289 responses out of 480 questionnaires administered, representing 60.2%. The data was analyzed using pie charts, bar charts, percentages, and line graphs. Findings revealed that the e-learning platforms were still useful. However, the students used it on a weekly basis post-COVID-19, unlike in the COVID-19 era, where it was used daily. All other academic activities, with the exception of examinations, are still undertaken on the e-learning platforms; however, it is underutilized in the post-COVID-19 experience. The study recommends that universities should invest in infrastructure development to enable all academic activities, most especially examinations, to be undertaken using the e-learning platforms to curtail future challenges.

Keywords: e-learning platform, undergraduate students, post-COVID-19 experience, public universities

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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: 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: Saulius Minkevicius, Edvinas Greicius

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The paper is devoted to the analysis of queueing systems in the context of the network and communications theory. We investigate the inequality in an open queueing network and its applications to the theorems in heavy traffic conditions (fluid approximation, functional limit theorem, and law of the iterated logarithm) for a queue of customers in an open queueing network.

Keywords: fluid approximation, heavy traffic, models of information systems, open queueing network, queue length of customers, queueing theory

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Authors: David Schafer

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Critical Theory is in sore need of a workable account of technology. It had one in the writings of Herbert Marcuse, or so it seemed until Jürgen Habermas mounted a critique in 'Technology and Science as Ideology' (Habermas, 1970) that decisively put it away. Ever since Marcuse’s work has been regarded outdated – a 'philosophy of consciousness' no longer seriously tenable. But with Marcuse’s view has gone the important insight that technology is no norm-free system (as Habermas portrays it) but can be laden with social bias. Andrew Feenberg is among a few serious scholars who have perceived this problem in post-Habermasian critical theory and has sought to revive a basically Marcusean account of technology. On his view, while so-called ‘technical elements’ that physically make up technologies are neutral with regard to social interests, there is a sense in which we may speak of a normative grammar or ‘technical code’ built-in to technology that can be socially biased in favor of certain groups over others (Feenberg, 2002). According to Feenberg, those perspectives on technology are reified which consider technology only by their technical elements to the neglect of their technical codes. Nevertheless, Feenberg’s account fails to explain what is normatively problematic with such reified views of technology. His plausible claim that they represent false perspectives on technology by itself does not explain how such views may be oppressive, even though Feenberg surely wants to be doing that stronger level of normative theorizing. Perceiving this deficit in his own account of reification, he tries to adopt Habermas’s version of systems-theory to ground his own critical theory of technology (Feenberg, 1999). But this is a curious move in light of Feenberg’s own legitimate critiques of Habermas’s portrayals of technology as reified or ‘norm-free.’ This paper argues that a better foundation may be found in Axel Honneth’s recent text, Freedom’s Right (Honneth, 2014). Though Honneth there says little explicitly about technology, he offers an implicit account of reification formulated in opposition to Habermas’s systems-theoretic approach. On this ‘normative functionalist’ account of reification, social spheres are reified when participants prioritize individualist ideals of freedom (moral and legal freedom) to the neglect of an intersubjective form of freedom-through-recognition that Honneth calls ‘social freedom.’ Such misprioritization is ultimately problematic because it is unsustainable: individual freedom is philosophically and institutionally dependent upon social freedom. The main difficulty in adopting Honneth’s social theory for the purposes of a theory of technology, however, is that the notion of social freedom is predicable only of social institutions, whereas it appears difficult to conceive of technology as an institution. Nevertheless, in light of Feenberg’s work, the idea that technology includes within itself a normative grammar (technical code) takes on much plausibility. To the extent that this normative grammar may be understood by the category of social freedom, Honneth’s dialectical account of the relationship between individual and social forms of freedom provides a more solid basis from which to ground the normative claims of Feenberg’s sociological account of technology than Habermas’s systems theory.

Keywords: Habermas, Honneth, technology, Feenberg

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Authors: Pinkey Yaqub

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The aim of this study was to investigate secondary (grades IX and X) students’ attitudes towards learning the English language based on the medium of instruction of the school, the gender of the students and the grade level in which they studied. A further aim was to determine students’ proficiency in the English language according to their gender, the grade level and the medium of instruction of the school. A survey was used to investigate the attitudes of secondary students towards English language learning. Simple random sampling was employed to obtain a representative sample of the target population for the research study as a comprehensive list of established English medium schools, and newly established English medium schools were available. A questionnaire ‘Attitude towards English Language Learning’ (AtELL) was adapted from a research study on Libyan secondary school students’ attitudes towards learning English language. AtELL was reviewed by experts (n=6) and later piloted on a representative sample of secondary students (n= 160). Subsequently, the questionnaire was modified - based on the reviewers’ feedback and lessons learnt during the piloting phase - and directly administered to students of grades 9 and 10 to gather information regarding their attitudes towards learning the English language. Data collection spanned a month and a half. As the data were not normally distributed, the researcher used Mann-Whitney tests to test the hypotheses formulated to investigate students’ attitudes towards learning English as well as proficiency in the language across the medium of instruction of the school, the gender of the students and the grade level of the respondents. Statistical analyses of the data showed that the students of established English medium schools exhibited a positive outlook towards English language learning in terms of the behavioural, cognitive and emotional aspects of attitude. A significant difference was observed in the attitudes of male and female students towards learning English where females showed a more positive attitude in terms of behavioural, cognitive and emotional aspects as compared to their male counterparts. Moreover, grade 10 students had a more positive attitude towards learning English language in terms of behavioural, cognitive and emotional aspects as compared to grade 9 students. Nonetheless, students of newly established English medium schools were more proficient in English as gauged by their examination scores in this subject as compared to their counterparts studying in established English medium schools. Moreover, female students were more proficient in English while students studying in grade 9 were less proficient in English than their seniors studying in grade 10. The findings of this research provide empirical evidence to future researchers wishing to explore the relationship between attitudes towards learning language and variables such as the medium of instruction of the school, gender and the grade level of the students. Furthermore, policymakers might revisit the English curriculum to formulate specific guidelines that promote a positive and gender-balanced outlook towards learning English for male and female students.

Keywords: attitude, behavioral aspect of attitude, cognitive aspect of attitude, emotional aspect of attitude

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Authors: Tecla Rita Karendi, Andy Cons Matata

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Although before and at the advent of colonial administration, several women such as Mekatilili wa Menza and Muthoni Nyanjiru took up leadership positions in resisting the colonial administration. Kenya is generally considered a patriarchal society. Many women who tried to take up positions of leadership in postcolonial Kenya, such as the Nobel Prize winner Wangari Maathai, were branded as prostitutes or generally immoral women. However, the Constitution of Kenya, 2010, has since made a huge impact not only in the area of affirmative action but also in various aspects of the feminist legal theory such as the constitutional requirement that no more than two-thirds of the members of the elective or appointive bodies should be of the same gender. This favours women who are often sidelined in elective posts such as parliament or county assemblies and state-appointed posts in the parastatals and commissions. The constitution also recognizes the right to abortion, which was outrightly outlawed in the independence constitution. Certain practices adverse to women’s health, such as wife inheritance, female genital mutilation, and property rights, are either outlawed or framed to recognized women’s rights. The education of the girl-child is also now considered a priority, unlike in the past. Despite these developments, a lot remains to be done.

Keywords: feminist legal theory, constitution of Kenya, 2010, affirmative action, leadership

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

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The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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Authors: Robertgie L. Pianar

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Post-colonial theory, post-colonialism, or Poco is a recently established literary theory. Consequently, not many literary works, local and international, have been subjected to its criticism. To help intellectualize local literary texts, in particular, through post-colonial discourse, this qualitative inquiry unfolded. Textual analysis was employed to describe, analyse, and interpret Doms Pagliawan’s Fire Extinguisher, a regional work of literature, grounded on the postcolonial concepts of Edward Said’s Otherness, Homi Bhabha’s Unhomeliness or Paralysis, and Frantz Fanon’s Cultural Resistance. The in-depth reading affirmed that the story contains those postcolonial attributes, revealing the following; (A) the presence of the colonizer, who successfully established colonial control over the colonized, the other, was found; (B) through power superimposition, the colonized character was silenced or paralyzed; and, (C) forms of cultural resistance from the colonized character were shown but no matter how its character avoids ‘postcolonial acts’, the struggle just intensifies, hence inevitable. Pagliawan’s Fire Extinguisher is thus a post-colonial text realizer between two differing cultures, the colonizer and the other. Results of this study may substantiate classroom discussions, both undergraduate and graduate classes, specifically in Philippine and World literature, 21st Century literature, readings in New English literatures, and literary theory and criticism courses, scaffolding learners’ grasp of post-colonialism as a major literary theory drawing classic exemplifications from this regional work.

Keywords: cultural resistance, otherness, post-colonialism, textual analysis, unhomeliness/paralysis

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Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour

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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning

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Authors: C. W. Kan, H. F. Cheung, Y. S. Lee

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This study examines the results of colour fading of cotton fabric by plasma-induced ozone treatment, with an aim to provide learning materials for fashion designers when designing colour fading effects in fashion products. Cotton knitted fabrics were dyed with red reactive dye with a colour depth of 1.5% and were subjected to ozone generated by a commercially available plasma machine for colour fading. The plasma-induced ozone treatment was conducted with different parameters: (i) air concentration = 10%, 30%, 50% and 70%; (ii) water content in fabric = 35% and 45%, and (iii) treatment time = 10 minutes, 20 minutes and 30 minutes. Finally, the colour properties of the plasma–induced ozone treated fabric were measured by spectrophotometer under illuminant D₆₅ to obtain the CIE L*, CIE a* and CIE b* values.

Keywords: learning materials, colour fading, colour properties, fashion products

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Authors: Bilal Ahmed, Muhammad Rafiq, Choongjae Im

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The tech-savvy Gen Z's transfer towards interactive concept learning is hammering the demand for online collaborative learning environments, renovating conventional education approaches. The authors propose a novel approach to enhance learning outcomes to improve retention in 3D interactive education by connecting virtual reality (VR) and non-VR devices in the classroom and distance learning. The study evaluates students' experiences with VR interconnectivity devices in human anatomy lectures using real-time 3D interactive data visualization. Utilizing the renowned "Guo & Pooles Inventory" and the "Flow for Presence Questionnaires," it used an experimental research design with a control and experimental group to assess this novel connecting strategy's effectiveness and significant potential for in-person and online educational settings during the sessions. The experimental group's interactions, engagement levels, and usability experiences were assessed using the "Guo & Pooles Inventory" and "Flow for Presence Questionnaires," which measure their sense of presence, engagement, and immersion throughout the learning process using a 5-point Likert scale. At the end of the sessions, we used the "Perceived Usability Scale" to find our proposed system's overall efficiency, effectiveness, and satisfaction. By comparing both groups, the students in the experimental group used the integrated VR environment and VR to non-VR devices, and their sense of presence and attentiveness was significantly improved, allowing for increased engagement by giving students diverse technological access. Furthermore, learners' flow states demonstrated increased absorption and focus levels, improving information retention and Perceived Usability. The findings of this study can help educational institutions optimize their technology-enhanced teaching methods for traditional classroom settings as well as distance-based learning, where building a sense of connection among remote learners is critical. This study will give significant insights into educational technology and its ongoing progress by analyzing engagement, interactivity, usability, satisfaction, and presence.

Keywords: interactive learning environments, human-computer interaction, virtual reality, computer- supported collaborative learning

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Weichen Chang

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To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice.

Keywords: artificial intelligence, task-oriented, contextualization, design education

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Authors: Jansirani Natarajan, Mickael Antoinne Joseph

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The COVID-19 pandemic has interrupted face-to-face education and forced universities into an emergency remote teaching curriculum over a short duration. This abrupt transition in the Spring 2020 semester left both faculty and students without proper preparation for continuing higher education in an online environment. Online learning took place in different formats, including fully synchronous, fully asynchronous, and blended in our university through the e-learning platform MOODLE. Studies have shown that students’ engagement, is a critical factor for optimal online teaching. Very few studies have assessed online engagement with ERT during the COVID-19 pandemic. Purpose: Therefore, this study, sought to understand how the sudden transition to emergency remote teaching impacted nursing students’ engagement with online courses in a Middle Eastern public university. Method: A cross-sectional descriptive research design was adopted in this study. Data were collected through a self-reported online survey using Dixon’s online students’ engagement questionnaire from a sample of 177 nursing students after the ERT learning semester. Results The maximum possible engagement score was 95, and the maximum scores in the domains of skills engagement, emotional engagement, participation engagement, and performance engagement were 30, 25, 30, and 10 respectively. Dixson (2010) noted that a mean item score of ≥3.5 (total score of ≥66.5) represents a highly engaged student. The majority of the participants were females (71.8%) and 84.2% were regular BSN students. Most of them (32.2%) were second-year students and 52% had a CGPA between 2 and 3. Most participants (56.5%) had low engagement scores with ERT learning during the COVID lockdown. Among the four engagement domains, 78% had low engagement scores for the participation domain. There was no significant association found between the engagement and the demographic characteristics of the participants. Conclusion The findings supported the importance of engaging students in all four categories skill, emotional, performance, and participation. Based on the results, training sessions were organized for faculty on various strategies for engaging nursing students in all domains by using the facilities available in the MOODLE (online e-learning platform). It added value as a dashboard of information regarding ERT for the administrators and nurse educators to introduce numerous active learning strategies to improve the quality of teaching and learning of nursing students in the University.

Keywords: engagement, perception, emergency remote learning, COVID-19

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of the acquisition of new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used, is the analysis of the dynamics of different areas of the brain during a cognitive activity to find the relationships between the different areas analyzed in order to better understand the functioning of neural networks. Also, the latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neuro-developmental difficulties for their subsequent assessment and cure. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, Learning disabilities, neural networks

Procedia PDF Downloads 122