Search results for: social learning

Authors: Laura Kahn, Paul Rodrigues, Onur Savas, Shannon Hahn

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An empirical understanding of an individual's personality expression can have a profound impact on organizations seeking to strengthen team performance and improve employee retention. A team's personality composition can impact overall performance. Creating a tiered information framework that leverages proxies for a user's social context and lexical and linguistic content provides insight into location-specific personality expression. We leverage the layered framework to examine domain-specific, psychological, and lexical cues within social media posts. We apply DistilBERT natural language transfer learning models with real world data to examine the relationship between Big Five personality expressions of people in Science, Technology, Engineering and Math (STEM) fields.

Keywords: big five, personality expression, social media analysis, workforce development

Procedia PDF Downloads 124

Authors: Jeffrey M. Byford

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The conceptualized theory of decision making on historical events often does not conform to uniform beliefs among students. When presented the opportunity, many students have differing opinions and rationales associated with historical events and outcomes. The intent of this paper was to provide students with the economic, social and political dilemmas associated with the autonomy of East Berlin. Students ranked seven possible actions from the most to least acceptable. In addition, students were required to provide both positive and negative factors for each decision and relative ranking. Results from this activity suggested that while most students chose a financial action towards West Berlin, some students had trouble justifying their actions.

Keywords: content-centered learning, cold war, Berlin, decision-making

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Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: Sara Moridpour

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Engineering students need to learn different software packages to meet the emerging industry needs. Face-to-face lectures provide an interactive environment for learning software packages. However, COVID changed expectations of face-to-face learning and teaching. It is essential to enhance the interaction among students and teachers in online and virtual learning and teaching of software packages. The proposed study introduces strategies for teaching engineering software packages in online and hybrid environments and evaluates students’ skills by an authentic assignment.

Keywords: teaching software packages, authentic assessment., engineering, undergraduate students

Procedia PDF Downloads 117

Authors: Bahloul Amel

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The present study debates students’ perceptions of the use of technology in learning English as a Foreign Language. Its aim is to explore and understand students’ preparation and presentation of Posters, PowerPoint and Animated Videos by drawing attention to visual and oral elements. The data is collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. The themes emerged from the data, visual learning satisfaction in using information and communication technology, providing structure to oral presentation, learning from peers’ presentations, draw attention to using Posters, PowerPoint and Animated Videos as each supports visual learning and organization of thoughts in oral presentations.

Keywords: EFL, posters, PowerPoint presentations, Animated Videos, visual learning

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Authors: Helene Jacobson Pettersson, Linda Lill

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Demographic changes and globalization in society provide new opportunities for social work and social work education in Sweden. There has been an ambition to include these aspects into the Swedish social work education. However, the Swedish welfare state standard continued to be as affectionate as invisible starting point in discussions about people’s way of life and social problems. The aim of this study is to explore content given to ethnic relations in social work in the social work education in Sweden. Our standpoint is that the subject can be understood both from individual and structural levels, it changes over time, varies in different steering documents and differs from the perspectives of teachers and students. Our question is what content is given to ethnic relations in social work by the teachers in their strategies and teaching material. The study brings together research in the interface between education science, social work and research of international migration and ethnic relations. The presented narratives are from longer interviews with a total of 17 university teachers who teach in social work program at four different universities in Sweden. The universities have in different ways a curriculum that involves the theme of ethnic relations in social work, and the interviewed teachers are teaching and grading social workers on specific courses related to ethnic relations at undergraduate and graduate levels. Overall assesses these 17 teachers a large number of students during a semester. The questions were concerned on how the teachers handle ethnic relations in education in social work. The particular focus during the interviews has been the teacher's understanding of the documented learning objectives and content of literature and how this has implications for their teaching. What emerges is the teachers' own stories about the educational work and how they relate to the content of teaching, as well as the teaching strategies they use to promote the theme of ethnic relations in social work education. The analysis of this kind of pedagogy is that the teaching ends up at an individual level with a particular focus on the professional encounter with individuals. We can see the shortage of a critical analysis of the construction of social problems. The conclusion is that individual circumstance precedes theoretical perspective on social problems related to migration, transnational relations, globalization and social. This result has problematic implications from the perspective of sustainability in terms of ethnic diversity and integration in society. Thus these aspects have most relevance for social workers’ professional acting in social support and empowerment related activities, in supporting the social status and human rights and equality for immigrants.

Keywords: ethnic relations in Swedish social work education, teaching content, teaching strategies, educating for change, human rights and equality

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Authors: Muneer Abbad

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This research explains the e-learning usage in a university in Jordan. Unified theory of acceptance and use of technology (UTAUT) model has been used as a base model to explain the usage. UTAUT is a model of individual acceptance that is compiled mainly from different models of technology acceptance. This research is the initial part from full explanations of the users' acceptance model that use Structural Equation Modelling (SEM) method to explain the users' acceptance of the e-learning systems based on UTAUT model. In this part data has been collected and prepared for further analysis. The main factors of UTAUT model has been tested as different factors using exploratory factor analysis (EFA). The second phase will be confirmatory factor analysis (CFA) and SEM to explain the users' acceptance of e-learning systems.

Keywords: e-learning, moodle, adoption, Unified Theory of Acceptance and Use of Technology (UTAUT)

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Authors: Amani Kappi, Ana Maria Linares, Gia Mudd-Martin

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Children with Attention Deficit Hyperactivity Disorder (ADHD) are more likely to develop social skills deficits that can lead to academic underachievement, peer rejection, and maladjustment. Surveying teachers about children's social skills with ADHD will become a significant factor in identifying whether the children will be diagnosed with social skills deficits. The teacher-specific version of the Social Skills Rating System scale (SSRS-T) has been used as a screening tool for children's social behaviors. The psychometric properties of the SSRS-T have been evaluated in various populations and settings, such as when used by teachers to assess social skills for children with learning disabilities. However, few studies have been conducted to examine the psychometric properties of the SSRS-T when used to assess children with ADHD. The purpose of this study was to examine the psychometric properties of the SSRS-T and two SSRS-T subscales, Social Skills and Problem Behaviors. This was a secondary analysis of longitudinal data from the Fragile Families and Child Well-Being Study. This study included a sample of 194 teachers who used the SSRS-T to assess the social skills of children aged 8 to 10 years with ADHD. Exploratory principal components factor analysis was used to assess the construct validity of the SSRS-T scale. Cronbach’s alpha value was used to assess the internal consistency reliability of the total SSRS-T scale and the subscales. Item analyses included item-item intercorrelations, item-to-subscale correlations, and Cronbach’s alpha value changes with item deletion. The results of internal consistency reliability for both the total scale and subscales were acceptable. The results of the exploratory factor analysis supported the five factors of SSRS-T (Cooperation, Self-control, Assertion, Internalize behaviors, and Externalize behaviors) reported in the original version. Findings indicated that SSRS-T is a reliable and valid tool for assessing the social behaviors of children with ADHD.

Keywords: ADHD, children, social skills, SSRS-T, psychometric properties

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Authors: Yafit Gabay

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Attention deficit hyperactivity disorder (ADHD) has been associated with both suboptimal functioning in the striatum and prefrontal cortex. Such abnormalities may impede the acquisition of perceptual categories, which are important for fundamental abilities such as object recognition and speech perception. Indeed, prior research has supported this possibility, demonstrating that children with ADHD have similar visual category learning performance as their neurotypical peers but use suboptimal learning strategies. However, much less is known about category learning processes in the auditory domain or among adults with ADHD in which prefrontal functions are more mature compared to children. Here, we investigated auditory and visual perceptual category learning in adults with ADHD and neurotypical individuals. Specifically, we examined learning of rule-based categories – presumed to be optimally learned by a frontal cortex-mediated hypothesis testing – and information-integration categories – hypothesized to be optimally learned by a striatally-mediated reinforcement learning system. Consistent with striatal and prefrontal cortical impairments observed in ADHD, our results show that across sensory modalities, both rule-based and information-integration category learning is impaired in adults with ADHD. Computational modeling analyses revealed that individuals with ADHD were slower to shift to optimal strategies than neurotypicals, regardless of category type or modality. Taken together, these results suggest that both explicit, frontally mediated and implicit, striatally mediated category learning are impaired in ADHD. These results suggest impairments across multiple learning systems in young adults with ADHD that extend across sensory modalities and likely arise from domain-general mechanisms.

Keywords: ADHD, category learning, modality, computational modeling

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Authors: Sari Myréen

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The aim of this study was to evaluate the role of multisensory elements in enhancing and facilitating foreign language acquisition among adult students in a language classroom. The use of multisensory elements enables the creation of a student-centered classroom, where the focus is on individual learner’s language learning process, perceptions and motivation. Multisensory language learning is a pedagogical approach where the language learner uses all the senses more effectively than in a traditional in-class environment. Language learning is facilitated due to multisensory stimuli which increase the number of cognitive connections in the learner and take into consideration different types of learners. A living lab called Multisensory Space creates a relaxed and receptive state in the learners through various multisensory stimuli, and thus promotes their natural foreign language acquisition. Qualitative and quantitative data were collected in two questionnaire inquiries among the Finnish students of a higher education institute at the end of their basic French courses in December 2014 and 2016. The inquiries discussed the effects of multisensory elements on the students’ motivation to study French as well as their learning outcomes. The results show that the French classes in the Multisensory Space provide the students with an encouraging and pleasant learning environment, which has a positive impact on their motivation to study the foreign language as well as their language learning outcomes.

Keywords: foreign language acquisition, pedagogical approach, multisensory learning, transcultural learning

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Authors: Ogoh Andrew Enokela

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This paper dwelt on the need for the utilization of instructional materials with highlights on the type of instructional materials, selection, uses and their importance on the learning and teaching of Agricultural Science Education in developing countries. It further discussed the concept of improvisation with some recommendation in terms of availability, utilization on the teaching and learning of Agricultural Science Education.

Keywords: instructional materials, agricultural science education, improvisation, teaching and learning

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Authors: Annelien A. Van Rooyen, Carol S. Binnekade, Deon Scott, Christina C. Shuttleworth

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Society expects professional accountants to uphold fundamental principles of professional competence, confidentiality, and ethical behavior. Their work needs to be trusted by the public, clients and other stakeholders. However, self-interest, intimidation and even ignorance could create conditions in which accounting practitioners and their staff may act contradictory to these principles. Similarly, plagiarism and cheating occur regularly at higher education institutions, where students claim ignorance of these actions and the accompanying consequences. Teaching students ethical skills in a distance-learning environment where interaction between students and instructors is limited is a challenge for academics. This also applies to instructors who teach accounting subjects to potential professional accountants. The researchers wanted to understand the concerns of accounting practitioners regarding recently qualified accounting students’ understanding of ethics and the resulting influence on their conduct. A mixed method approach was used to obtain feedback from numerous accounting practitioners in South Africa. The research questions focused mainly on ethical conduct in the workplace and the influence of social media on the behavior of graduates. The findings of the research suggested, inter alia, that accounting practitioners are of the opinion that the ethical conduct of graduates starts at home, but higher education institutions play a pivotal role in providing students with an understanding of ethics in the workplace, including the role of social media. The paper concludes with recommendations on how academics in higher education institutions need to address these challenges.

Keywords: accounting profession, distance learning, ethics, workplace

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Authors: Songul Cinaroglu

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Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

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Authors: Ting Hsiang Chang

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Nowadays in Taiwan, higher education, which was previously more emphasized on teaching-oriented approaches, has gradually shifted to an approach more focusing on students learning outcomes. With student employment rate as an important indicator for University Program Evaluation periodically held by the Ministry of Education, it becomes extremely critical for a university to build up a teaching and learning quality assurance system to bridge the gap between learning and practice. Teaching and Learning Quality Assurance System has been built and implemented at Chaoyang University of Technology for years and has received substantial results. By employing various forms of evaluation and performance appraisals, the effectiveness of teaching and learning can consistently be tracked as a means of ensuring teaching and learning quality. This study aims to explore the evaluation system of teaching and learning quality assurance system at the Chaoyang University of Technology by means of content analysis. The study contents the evaluation reports on the teaching and learning quality assurance at the Chaoyang University of Technology in the Academic Year 2013-2015. The quantitative results of the assessment were analyzed using the five-point Likert Scale. Quality assurance Committee meetings were further held for examining and discussions on the results. To the end, the annual evaluation report is to be produced as references used to improve approaches in both teaching and learning. The findings indicate that there is a respective relationship between the overall teaching evaluation items and the teaching goals and core competencies. In addition, graduates’ feedbacks were also collected for further analysis to examine if the current educational planning is able to achieve the university’s teaching goal and cultivation of core competencies.

Keywords: core competencies, teaching and learning quality assurance system, teaching goals, university program evaluation

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Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharana

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Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: computer assisted learning, intelligent tutoring system, learner centered design, mobile mediated learning and teacher education

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Authors: Mukhtar Raban

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Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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Authors: Yessica A. Aguilera

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English is currently the only foreign language included in the national educational curriculum in Chile. The English curriculum establishes that once completed secondary education, students are expected to reach B1 level according to the Common European Reference Framework (CEFR) scale. However, the objective has not been achieved, and to the author’s best knowledge, there is still a severe lack of English language skills among students who have completed their secondary education studies. In order to deal with the fact that students do not manage English as expected, team-based learning (TBL) was introduced in English language lessons at the Universidad Federico Santa María (USM). TBL is a collaborative teaching-learning method which enhances active learning by combining individual and team work. This approach seeks to help students achieve course objectives while learning how to function in teams. The purpose of the research was to assess the implementation and effectiveness of TBL in English language classes at USM technical training education. Quantitative and qualitative data were collected from teachers and students about their experience through TBL. Research findings show that both teachers and students are satisfied with the method and that students’ engagement and participation in class is higher. Additionally, students score higher on examinations improving academic outcomes. The findings of the research have the potential to guide how TBL could be included in future English language courses.

Keywords: collaborative learning, college education, English language learning, team-based learning

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Brooke A. Moore

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Developing teachers’ cultural awareness ensures schools are culturally responsive and socially just for diverse and exceptional students. An ideology of ‘normal’ exists in schools, creating boundaries where some students belong and others are marginalized based on difference. It is important that teacher preparation work to create democratic classrooms where teachers foster tolerance of difference and promote critical thinking and social justice. This paper outlines a framework for developing educator cultural awareness through the use of critically reflective professional learning communities (PLCs) drawing from the research on teacher critical reflection, collaborative PLCs, and Engeström’s theory of expansive learning. A case study using the framework was conducted with ten practicing teachers. Participants read and reflected on critical literature to make visible unexamined beliefs, engaged in conversations that pushed them to reflect more deeply and project forward new ideas, and set goals for acting as agents of change in their schools.

Keywords: cultural and linguistic diversity, diversity, special education, teacher beliefs

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: kindergarten, child, learning resources, QR code, smart phone, mobile

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Authors: Evmorfia Koukia, Polyxeni Mangoulia

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Workshops tend to be a vivid and productive way as an in vivo teaching method. Due to the pandemic, COVID-19 university courses were conducted through the internet. Method It was tried for the first time to integrate online art therapy workshops in a core course named “Special Themes of Mental Health Nursing” in a MSc Program in Mental Health. The duration of the course is 3-hours per week for 11 weeks in a single semester. The course has a main instructor, a professor of psychiatric nursing experienced in arts therapies workshops and visiting art therapists. All art therapists were given a certain topic to cover. Students were encouraged to keep a logbook that was evaluated at the end of the semester and was submitted as a part of the examination process of the course. An interview of 10 minutes was conducted with each student at the end of the course from an independent investigator (an assistant professor) Participants The students (sample) of the program were: nurses, psychologists, and social workers Results: All students who participated in the courses found that the learning process was vivid, encouraging participation and self-motivation, and there were no main differences from in vivo learning. The students identified their personal needs, and they felt a personal connection with the learning experience. The result of the personalized learning was that students discovered their strengths and weaknesses and developed skills like critical thinking. All students admitted that the workshops were the optimal way for them to comprehend the courses’ content, their capability to become therapists, as well as their obstacles and weaknesses while working with patients in mental health. Conclusion: There were no important differences between the views of students in online and in vivo teaching method of the workshops. The result has shown that workshops in mental health can contribute equally in the learning experience.

Keywords: mental health, workshops, students, nursing

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Peter Adekunle, Clinton Aigbavboa, Matthew Ikuabe, Opeoluwa Akinradewo

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The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment.

Keywords: machine learning, implementation, built environment, construction stakeholders

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Authors: Waraporn Thaimit, Yuwadee Insamran, Natchanok Jansawang

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Focusing on Analytical Thinking and Learning Achievement are the critical component of visual thinking that gives one the ability to solve problems quickly and effectively that allows to complex problems into components, and the result had been achieved or acquired form of the subject students of which resulted in changes within the individual as a result of activity in learning. The aims of this study are to administer on comparisons between students’ analytical thinking abilities and their learning achievements sample size consisted of 80 students who sat at the 12th grade level in 2 classes from Chaturaphak Phiman Ratchadaphisek School, the 40-student experimental group with the Problem-Based Learning (PBL) and 40-student controlling group with the Concept Mapping Instructional (CMI) methods were designed. Research instruments composed with the 5-lesson instructional plans to be assessed with the pretest and posttest techniques on each instructional method. Students’ responses of their analytical thinking abilities were assessed with the Analytical Thinking Tests and students’ learning achievements were tested of the Learning Achievement Tests. Statistically significant differences with the paired t-test and F-test (Two-way MANCOVA) between post- and pre-tests of the whole students in two chemistry classes were found. Associations between student learning outcomes in each instructional method and their analytical thinking abilities to their learning achievements also were found (ρ < .05). The use of two instructional methods for this study is revealed that the students perceive their abilities to be highly learning achievement in chemistry classes with the PBL group ought to higher than the CMI group. Suggestions that analytical thinking ability involves the process of gathering relevant information and identifying key issues related to the learning achievement information.

Keywords: comparisons, students learning achievements, analytical thinking abilities, the problem-based learning method, the concept mapping instructional method, gene and chromosome issue, chemistry classes

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Authors: Edu Marcelina, Sule Sheidu A., Nsor Eunice

Abstract:

As open and distance education is gradually becoming an acceptable means of solving the problem of access in higher education, quality has now become one of the main concerns among institutions and stakeholders of open and distance learning (ODL) and the education sector in general. This study assessed the challenges of academic quality in the open and distance learning (ODL) education in Nigeria using Distance Learning Institute (DLI), University of Lagos and National Open University of Nigeria as a case. In carrying out the study, a descriptive survey research design was employed. A researcher-designed and validated questionnaire was used to elicit responses that translated to the quantitative data for this study. The sample comprised 665 students of the Distance Learning Institute (DLI), and National Open University of Nigeria (NOUN), carefully selected through the method of simple random sampling. Data collected from the study were analyzed using Chi-Square (X2) at 0.05 Level of significance. The results of the analysis revealed that; the use of ICT tools is a factor in ensuring quality in the Open and Distance Learning (ODL) operations; the quality of the materials made available to ODL students will determine the quality of education that will be received by the students; and the time scheduled for students for self-study, online lecturing/interaction and face to face study and the quality of education in Open and Distance Learning Institutions has a lot of impact on the quality of education the students receive. Based on the findings, a number of recommendations were made.

Keywords: open and distance learning, quality, ICT, face-to-face interaction

Procedia PDF Downloads 354

Authors: Abdelaziz Hussien

Abstract:

This article reports investigations of a study into the effectiveness of a traits cooperative learning (TCL) on teacher candidates’ writing achievement, composition, and attitudes towards traits of writing approach and small group learning. Mixed methodologies were used with the participants in a repeated measures quasi-experimental design. Forty-two class teacher candidates, enrolled in the Bahrain Teachers College, completed the pre and post author-developed measures. The results suggest that TCL has a positive effect on the participants’ writing achievement, composition, and attitudes towards traits of writing approach, but not on the attitudes towards small group learning. Further implications to teacher education are presented.

Keywords: trait-based language education, cooperative learning, writing achievement, writing composition, traits of writing, teacher education

Procedia PDF Downloads 142

Authors: Peggy S. C. van Teunenbroek

Abstract:

Recently, philanthropic crowd-funding -the raising of external funding from a large audience via social networks or social media- emerged as a new funding instrument for the Dutch cultural sector. However, such philanthropic crowdfunding in the US and the Netherlands is less successful than any other form of crowdfunding. We argue that social aspects are an important stimulus in philanthropic crowd-funding since previous research has shown that crowdfunding is stimulated by something beyond financial merits. Put simply, crowd-funding seems to be a socially motivated activity. In this paper we focus on the effect of social information, described as information about the donation behavior of previous donors. Using a classroom experiment we demonstrated a positive effect of social information on the donation behavior in crowdfunding campaigns. Our study extends previous research by showing who is affected by social information and why, and highlights how social information can be used to stimulate individuals to donate more to crowdfunding projects.

Keywords: online donation behavior, philanthropic crowdfunding, social information, social influence, social motivation

Procedia PDF Downloads 383