Search results for: region weight learning

Authors: Jose Ramon Calvo-Ferrer

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Video games have been extensively employed in educational contexts to teach contents and skills, upon the premise that they engage students and provide instant feedback, which makes them adequate tools in the field of education and training. Term frequency, along with metacognition and implicit corrective feedback, has often been identified as powerful variables in the learning of vocabulary in a foreign language. This study analyses the learning of L2 mobile operating system terminology by a group of students and uses the data collected by the video game The Conference Interpreter to identify the predictive strength of term frequency (times a term is shown), positive metacognition (times a right answer is provided), and negative metacognition (times a term is shown as wrong) regarding L2 vocabulary learning and perceived learning outcomes. The regression analysis shows that the factor ‘positive metacognition’ is a positive predictor of both dependent variables, whereas the other factors seem to have no statistical effect on any of them.

Keywords: digital game-based learning, feedback, metacognition, frequency, video games

Procedia PDF Downloads 157

Authors: Bindya Jacob

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The aim of the present study was to assess the quality of catchup growth induced by Oral Nutrition Supplement (ONS), in animal model of growth restriction due to under nutrition. Quality of catch-up growth was assessed by proportion of lean body mass (LBM) and fat mass (FM). Young SD rats were food restricted at 70% of normal caloric intake for 4 weeks; and re-fed at 120% of normal caloric intake for 4 weeks. Refeeding diet had 50% calories from animal diet and 50% from ONS formulated for optimal growth. After refeeding, the quantity and quality of catch-up growth were measured including weight, length, LBM and FM. During nutrient restriction, body weight and length of animals was reduced compared to healthy controls. Both LBM and FM were significantly lower than healthy controls (p < 0.001). Refeeding with ONS resulted in increase of weight and length, with significant catch-up growth compared to baseline (p < 0.001). Detailed examination of body composition showed that the catch-up in body weight was due to proportionate increase of LBM and FM, resulting in a final body composition similar to healthy controls. This data supports the use of well-designed ONS for recovery from growth restriction due to under nutrition, and return to normal growth trajectory characterized by normal ratio of lean and fat mass.

Keywords: catch up growth, body composition, nutrient restriction, healthy growth

Procedia PDF Downloads 438

Authors: Rudolf Egger

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This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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Authors: G. Karakaya, C. Türker, M. Anaklı

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It is necessary to test to see if optical devices such as camera, night vision devices are working properly. Therefore, a precision biaxial rotary system (gimbal) is required for mounting Unit Under Test, UUT. The Gimbal systems can be utilized for precise positioning of the UUT; hence, optical test can be performed with high accuracy. The weight of UUT, which is placed outside the axis of rotation, causes an off-axis moment to the mounting armature. The off-axis moment can act against the direction of movement for some orientation, thus the electrical motor, which rotates the gimbal axis, has to apply higher level of torque to guide and stabilize the system. Moreover, UUT and its mounting fixture to the gimbal can be changed, which causes change in applied resistance moment to the gimbals electrical motor. In this study, a preloaded spring is added to the gimbal system for minimizing applied off axis moment with the help of four bar mechanism. Two different possible methods for preloading spring are introduced and system optimization is performed to eliminate all moment which is created by off axis weight.

Keywords: adaptive, balancing, gimbal, mechanics, spring

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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 143

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: 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: Zafar Iqbal

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This study involved students of 6th semester enrolled in a Bachelor of Computer Science Program at university level. In this era of science and technology, e-learning can be helpful for grassroots in providing them access to education tenant in less developed areas. It is a potential substitute of face-to-face teaching being used in different countries. The purpose of the study was to explore the views of students about e-learning (Facebook) as an instructional tool. By using purposive sampling technique an intact class of 30 students included both male and female were selected where e-learning was used as an instructional tool. The views of students were explored through qualitative approach by using focus group interviews. The approach was helpful to develop comprehensive understanding of students’ views towards e- learning. In addition, probing questions were also asked and recorded. Data was transcribed, generated nodes and then coded text against these nodes. For this purpose and further analysis, NVivo 10 software was used. Themes were generated and tangibly presented through cluster analysis. Findings were interesting and provide sufficient evidence that face book is a subsequent e-learning source for students of higher education. Students acknowledged it as best source of learning and it was aligned with their academic and social behavior. It was not time specific and therefore, feasible for students who work day time and can get on line access to the material when they got free time. There were some distracters (time wasters) reported by the students but can be minimized by little effort. In short, e-learning is need of the day and potential learning source for every individual who have access to internet living at any part of the globe.

Keywords: e-learning, facebook, instructional tool, higher education

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Authors: Yıldırım I. Tosun, Halim Cevizci, Hakan Ceylan

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By GEO5 FEM program with four rockfill slope modeling and stability analysis was performed for S1, S2, S3 and S4 slopes where landslides of the shalefills were limited. Effective angle of internal friction (φ'°) 17°-22.5°, the effective cohesion (c') from 0.5 to 1.8 kPa, saturated unit weight 1.78-2.43 g/cm3, natural unit weight 1.9-2.35 g/cm3, dry unit weight 1.97-2.40 g/cm3, the permeability coefficient of 1x10-4 - 6.5x10-4 cm/s. In cross-sections of the slope, GEO 5 FEM program possible critical surface tension was examined. Rockfill dump design was made to prevent sliding slopes. Bulk material designated geotechnical properties using also GEO5 programs FEM and stability program via a safety factor determined and calculated according to the values S3 and S4 No. slopes are stable S1 and S2 No. slopes were close to stable state that has been found to be risk. GEO5 programs with limestone rock fill dump through FEM program was found to exhibit stability.

Keywords: slope stability, stability analysis, rockfills, sock stability

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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: 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: Rui Lança, Elisa Silva, Fátima Farinha, Miguel José Oliveira, Manuel Duarte Pinheiro, Cátia Miguel

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Tourism has a great potential to bring up progress across the Sustainable Development Goals (SDGs). If well managed and monitored, the tourism sector can create quality jobs, reduce poorness and offer incentives for environmental preservation, helping on the transition towards more inclusive and resilient economies. However, without proper safeguards and investments, expansion of the tourism market will increase pressure on biodiversity and the ecosystems on which the livelihoods of local communities depend. Competitivity is a key dimension in tourism, sustainable tourism challenge new dimensions to competitivity, namely environmental, social, institutional and economic achieve a medium and long-term competitivity. It is undoubtedly clear on the tourism sector, the importance of the region sustainability in the current touristic destinations offer. The basis of a tourism region prosperity will depend on /of it. The OBSERVE project intends to be an instrument for monitoring and evaluating the sustainability levels of the Algarve region. Its main objective is to provide environmental, economic, social-cultural and institutional indicators to support the decision-making process for a sustainable growth of the region. The project´s main goal is a digital portal with the most relevant indicators to allow evaluating and communicating the performance of the region in a sustainable growth perspective. This paper presents the OBSERVE project and highlights the potential contribution to a broad perspective of competitivity and its contribution for different stakeholders and the touristic value chain. Limitations and opportunities are also discussed.

Keywords: sustainable tourism, competitivity, OBSERVE project, Algarve region

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Authors: Abrha Reta, Ajebu Nurfeta, Genet Mengistu, Mohammed Beyan

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Fodder trees such as Ziziphus spina-christi have the potential to enhance the utilization of natural grazing resources and also to mitigate seasonal feed shortages. The experiment was conducted with the objective of evaluating the effect of supplementing Ziziphus spina-christi leaf meal (ZSCLM) to natural pasture hay on feed intake, body weight gain, digestibility, and carcass characteristics of Tigray highland sheep. A randomized complete block design was employed with 5 blocks based on initial body weight, and sheep were randomly assigned to five treatments. Treatments were: 100g concentrate mix + ad libtum natural pasture hay (T1), T1+ 100g ZSCLM (T2), T1 + 200g ZSCLM (T3), T1 + 300g ZSCLM (T4), and T1 + 400g ZSCLM (T5) on dry matter (DM) basis. Dry matter intake was greater (P<0.05) in sheep on T5 compared to T3 and T1, while the total DM intake among T2, T4, and T5 were similar. Crude protein and metabolizable energy intake differed (P<0.05) among treatments with highest and lowest values in T5 and T1, respectively. Average daily gain was higher (P<0.05) in sheep kept on T2, T3, and T4 diets than T1. Higher (P<0.05) DM digestibility was found in T4 and T5 than T1. The highest (P<0.05) OM and CP digestibility was observed in sheep fed T3, T4, and T5 diets. Rib eye muscle area was higher (P<0.05) for T4 than T1 and T2. Dressing percentage was similar (P>0.05) among treatments. The current study indicated that supplementation of Tigray highland sheep with 200g air-dried Ziziphus spina-christi leaf meal leaves with 100g of concentrate mixture in their diet significantly increased feed intake and apparent digestibility, body weight gain, hot carcass weight, and rib eye muscle area by improving feed conversion efficiency.

Keywords: body weight, carcass, digestibility, and ziziphus spina-christi leaf meal

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Authors: Christopher J. Johnston

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This paper presents the finding of a research study in which novice (first and second year) elementary teachers (grades Kindergarten – six) evaluated various mathematics Virtual Manipulatives, websites, and Applets (tools) for use in mathematics instruction. Participants identified the criteria they used for evaluating these types of resources and provided recommendations for or against five pre-selected tools. During the study, participants participated in three data collection activities: (1) A brief Likert-scale survey which gathered information about their attitudes toward technology use; (2) An identification of criteria for evaluating technology tools; and (3) A review of five pre-selected technology tools in light of their self-identified criteria. Data were analyzed qualitatively using four theoretical categories (codes): Software Features (41%), Mathematics (26%), Learning (22%), and Motivation (11%). These four theoretical categories were then grouped into two broad categories: Content and Instruction (Mathematics and Learning), and Surface Features (Software Features and Motivation). These combined, broad categories suggest novice teachers place roughly the same weight on pedagogical features as they do technological features. Implications for mathematics teacher educators are discussed, and suggestions for future research are provided.

Keywords: mathematics education, novice teachers, technology, virtual manipulatives

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Authors: Kivilcim Ersoy, Cansu Yazganarikan

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In recent years, composite materials are more frequently utilized not only in aviation but also in automotive industry due to its high strength to weight ratio, fatigue and corrosion resistances as well as better performances in specific environments. The market demand also favors lightweight design for wheeled and tracked armored vehicles due to the increased demand for land and amphibious mobility features. This study represents the current application areas and trends in automotive, bus and armored land vehicles industries. In addition, potential utilization areas of fiber composite and hybrid material concepts are being addressed. This work starts with a survey of current applications and patent trends of composite materials in automotive and land vehicle industries. An intensive investigation is conducted to determine the potential of these materials for application in land vehicle industry, where small series production dominates and challenging requirements are concerned. In the end, potential utilization areas for combat land vehicle systems are offered. By implementing these light weight solutions with alternative materials and design concepts, it is possible to achieve drastic weight reduction, which will enable both land and amphibious mobility without unyielding stiffness and survivability capabilities.

Keywords: land vehicle, composite, light-weight design, armored vehicle

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Authors: Nurul Z. Sani, Amalina N. Ghazali, Azree Elmy, Lee C. Yuen, Zar C. Thent

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Piper betel (P. betel) leaves is widely used in Asian countries for treating diabetes mellitus and its complication. In our previous study, we observed the positive effect of P.betel extract on diabetic wounds following 3 and 7 days of treatment. The aim of the present study was to determine the effect of P.betel leaves extract in the diabetic rats was observed in terms of body weight and wound contraction rates following 5 days of the treatment. Total 64 male Sprague-Dawley rats were used and the experimental rats received a single dose of 60mg/kg of Streptozotocin (STZ) injection, intraperitoneally. Four full thickness (6mm) cutaneous wounds were created on dorsum of each rat. The rats were divideid into (n=8): Non-treated Control (NC), Non-treated Diabetic (ND), diabetic treated with commercial cream (SN) and diabetic treated with 50mg/kg of P.betel extract (PB). The rats were sacrificed on day 0 and 5 post wounding. Significant increased in wound closure rate, body weight was observed in PB group compared to ND. Histological deterioration was restored in the P. betel extract treated wounds. It is concluded that topical application with P.betel extract for 5 days of post wounding offers positive scientific value in diabetic rats.

Keywords: diabetes, piper betel, wound healing, body weight, morphology

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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: Ezaldin A. M. Mohammed, Youssef K. H. Abdalhafid, Masoud. M. Zatout

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The study aims to clarify the toxic effect of plant hormones, which are widely used in agriculture. One of these is the plant hormones (indole acetic acid); has been ٳata hormone to rats at 100 ppm salt solution of 0.2 per day after day for a period of forty days before conception until the fourteenth day or sixteenth or childbirth. Treatment brought about a marked shortage in the rate of increase in the weight of mice., And a percentage of the weight of the liver there was a distinct increase in the relative weight of the liver. As well as the increase in pathological changes and increase the size of the nuclei and Kupffer cell, as noted widespread and dense clusters of inflammatory cells accompanied by about the erosion of liver tissue and blood ٳrchah. Biochemical analyzes showed a marked decrease of the liver in antioxidant enzymes and an increase in the rate of free radicals. It was also noted an increase in cases of abortion. The owner of so many birth defects. It was also noted the lack of body weight in fetuses and increase the absorption rate of embryos in fetuses of mothers treatment compared to the control group. Showed microscopic examinations of the liver of mice born in the transaction and the decay in the presence of hepatic cells and edema, blood vessels and increase the rate of cell death.

Keywords: indol acetic acid, liver, pathological changes, albino rats

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: e-learning system, gamification, motivation, social comparison, visualization

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Authors: Jonmichael Weaver, David Miller

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Dyneema is an ultra-high molecular weight polyethylene (UHMWPE) fiber created by DSM. This fiber has many applications due to the high tensile strength, low weight, and inability to absorb water. DSM manufactures a non-woven unidirectional cross-ply [0,90]2 lamina, using the Dyneema fiber. Using this lamina system, various thickness panels are created for a 40% lighter weight alternative to Kevlar for the same ballistics protection. Environmental effects on the ply/laminate system alter the material properties, resulting in diminished ultimate performance. Understanding the specific environmental parameters and characterizing the resulting material property degradation is essential for determining the safety and reliability of Dyneema in service. Two laminas were contrasted for their response to accelerated aging by UV, humidity, and temperature cycling. Both lamina contain the same fiber, SK-99, but differ in matrix composition, Dyneema HB-210 employs a polyurethane (PUR) based matrix, and HB-212 contains a rubber-based matrix. Each system was inspected using a scanning electron microscope (SEM) and evaluated by dynamic mechanical analysis (DMA) to characterize the material property changes alongside the corresponding composite damage and matrix failure mode over the aging parameters. Overall, resulting in the HB-212 degrading faster compared with the HB-210.

Keywords: dyneema, accelerated aging, polymers, ballistics protection, armor, DSM, kevlar, composites

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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: Aliseydi Bozkurt, Ugur Yılmaz

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Objective: It was aimed to evaluate the current status of semen parameters in fertile males with one or more children and whose wife having a pregnancy for the last 1-12 months in Malatya region. Methods: Sperm samples were obtained from 131 voluntary fertile men. In each analysis, sperm volume (ml), number of sperm (sperm/ml), sperm motility and sperm viscosity were examined with Makler device. Classification was made according to World Health Organization (WHO) criteria. Results: Mean ejaculate volume ranged from 1.5 ml to 5.5 ml, sperm count ranged from 27 to 180 million/ml and motility ranged from 35 to 90%. Sperm motility was found to be on average; 69.9% in A, 7.6% in B, 8.7% in C, 13.3% in D category. Conclusion: The mean spermiogram values of fertile males in Malatya region were found to be similar to those in fertile males determined by the WHO. This study has a regional classification value in terms of spermiogram values.

Keywords: fertile men, infertility, spermiogram, sperm motility

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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: Samira Rabiei, Faezeh Askari, Reza Rastmanesh

Abstract:

Objective: To evaluate the effects of nutrition education and adherence to a healthy diet on glycemic and lipidemic control in patients with T2DM. Material and Methods: A randomized controlled trial was conducted on 494 patients with T2DM, aged 14-87 years from both sexes who were selected by convenience sampling from referees to Aliebneabitaleb hospital in Ghom. The participants were divided into two 247 person groups by stratified randomization. Both groups received a diet adjusted based on ideal body weight, and the intervention group was additionally educated about healthy food choices regarding diabetes. Information on medications, psychological factors, diet and physical activity was obtained from questionnaires. Blood samples were collected to measure FBS, 2 hPG, HbA1c, cholesterol, and triglyceride. After 2 months, weight and biochemical parameters were measured again. Independent T-test, Mann-Whitney, Chi-square, and Wilcoxon were used as appropriate. Logistic regression was used to determine the odds ratio of abnormal glycemic and lipidemic control according to the intervention. Results: The mean weight, FBS, 2 hPG, cholesterol and triglyceride after intervention were significantly lower than before that (p < 0.05). Discussion: Nutrition education plus a weigh reducer diet is more effective on glycemic and lipidemic control than a weight reducer diet, alone.

Keywords: type 2 diabetes mellitus, nutrition education, glycemic control, lipid profile

Procedia PDF Downloads 209

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

Abstract:

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

Procedia PDF Downloads 358