Search results for: learning content

Authors: Ali Shah

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This paper outlines the case study experience of using a variety of online strategies in an Australian music academy context during covid times. The study aimed at exploring how online applications help students to learn music, specifically playing musical instruments, composing songs, and performing virtually. To explore this, music teachers’ perceptions and experiences regarding online learning, the teaching strategies they implemented, and the challenges they faced were examined. For the purpose of this study, a qualitative research structure was adopted through the use of three data collection tools. These methods included pre- and post-research individual interviews of teachers and students, analysis of their lesson plans, virtual classroom observations of the teachers followed by the researcher’sown reflections, post-observation discussions, and teachers’ reflective journals. The findings revealed that teachers had a theoretical understanding of virtual learning and recent musical application such as Flowkey, Skoove, and Piano marvel, which are benefits of e-learning. While teachers faced challenges in implementing strategies to teach keyboard/piano online, overall, both students and teachers felt the positive impact of online applications and strategies on their learning and felt that modern technology made it possible for anyone to take music lessons at home.

Keywords: music, keyboard, piano, online learning, virtual learning

Procedia PDF Downloads 75

Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

Procedia PDF Downloads 174

Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju

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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.

Keywords: school climate, parental involvement, ODL, learning gains, mathematics

Procedia PDF Downloads 522

Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

Procedia PDF Downloads 243

Authors: Xinyi Le

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In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

Procedia PDF Downloads 438

Authors: G. E. Gandomkar, E. Bekhradinassab, S. Sabbaghi, M. M. Zerafat

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The reduction of water content in crude oil emulsions reduces pipeline corrosion potential and increases the productivity. Chemical emulsification of crude oil emulsions is one of the methods available to reduce the water content. Presence of demulsifier causes the film layer between the crude oil emulsion and water droplets to become unstable leading to the acceleration of water coalescence. This research has been performed to study the improvement performance of a chemical demulsifier by silica nanoparticles. The silica nano-particles have been synthesized by sol-gel technique and precipitation using poly vinyl alcohol (PVA) and poly ethylene glycol (PEG) as surfactants and then nano-particles are added to the demulsifier. The silica nanoparticles were characterized by Particle Size Analyzer (PSA) and SEM. Upon the addition of nanoparticles, bottle tests have been carried out to separate and measure the water content. The results show that silica nano-particles increase the demulsifier efficiency by about 40%.

Keywords: demulsifier, dehydration, silicon dioxide, nanoparticle

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Authors: Zolzaya Badmaavanchig, Shoko Miyamoto

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In recent years, universal design for learning (hereinafter referred to as "UDL"), which aims to establish an inclusive education system and to make all children, regardless of their disabilities, experts in learning, has been attracting attention, and there have been some attempts to incorporate it into regular classrooms where children with developmental disabilities and those who show such tendencies are enrolled. The purpose of this study was to examine the effectiveness and challenges of implementing UDL in Japanese elementary schools based on the previous literature. As a method, we first searched for articles on UDL for learning and UDL in the classroom from 2010 to 2022. In addition, we selected practice studies that targeted children with special educational support needs and the classroom as a whole. In response to the extracted literature, this bridge examined the following five perspectives: (1) subjects and grades in which UDL was practiced, (2) methods to grasp the actual conditions of the children, (3) consideration for children with special needs during class, (4) form of class, and (5) effects of the practice. Based on the results, we would like to present issues related to future UDL efforts in Japanese elementary schools.

Keywords: universal design for learning, regular elementary school class, children with special education needs, special educational support

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Authors: Adam Wiryawan

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The levels of micro metal elements in the soil are influenced by soil management. In this research, the influence of soil management on the content of micro metal elements in the soil in the UB forest was studied. The metals studied include Zn, Mn, Cu, Fe, Cd, and Pb. Soil samples were taken from five sampling points on soil in the UB forest, both soils tilled and untilled. Before analysis, soil samples were digested with HNO₃ solution, and metal levels in soil samples were measured using atomic absorption spectrometry (AAS). The results of the analysis of metal content in the soil at the UB forest show that tilled land has consistently lower levels of metals like Zn, Mn, Cu, and Fe compared to untilled land. Meanwhile, Pb and Cd metals were not detected in all soil samples.

Keywords: soil treatment, metal content, forest soil, Malang District

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Authors: Haruya Tamaki, Tsugunosuke Sakai, Ryuichi Yoshida, Ryohei Egusa, Shigenori Inagaki, Etsuji Yamaguchi, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi

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Art appreciation is important as part of children education. Art appreciation can enrich sensibility and creativity. To enrich sensibility and creativity, the children have to learning knowledge of picture such as social and historical backgrounds and author intention. High learning effect can acquire by actively learning. In short, it is important that encourage learning of the knowledge about pictures actively. It is necessary that children feel like interest to encourage learning of the knowledge about pictures actively. In a general art museum, comments on pictures are done through writing. Thus, we expect that this method cannot arouse the interest of the children in pictures, because children feel like boring. In brief, learning about the picture information is difficult. Therefore, we are developing an art-appreciation support system that will encourage learning of the knowledge about pictures actively by children feel like interest. This system uses that Interacting with Pictures to learning of the knowledge about pictures. To Interacting with Pictures, children have to utterance by themselves. We expect that will encourage learning of the knowledge about pictures actively by Interacting with Pictures. To more actively learning, children can choose who talking with by information that location and movement of the children. This system must be able to acquire real-time knowledge of the location, movement, and voice of the children. We utilize the Microsoft’s Kinect v2 sensor and its library, namely, Kinect for Windows SDK and Speech Platform SDK v11 for this purpose. By using these sensor and library, we can determine the location, movement, and voice of the children. As the first step of this system, we developed ukiyo-e game that use ukiyo-e to appreciation object. Ukiyo-e is a traditional Japanese graphic art that has influenced the western society. Therefore, we believe that the ukiyo-e game will be appreciated. In this study, we applied talking to pictures to learn information about the pictures because we believe that learning information about the pictures by talking to the pictures is more interesting than commenting on the pictures using only texts. However, we cannot confirm if talking to the pictures is more interesting than commenting using texts only. Thus, we evaluated through EDA measurement whether the user develops an interest in the pictures while talking to them using voice recognition or by commenting on the pictures using texts only. Hence, we evaluated that children have interest to picture while talking to them using voice recognition through EDA measurement. In addition, we quantitatively evaluate that enjoyed this game or not and learning information about the pictures for primary schoolchildren. In this paper, we summarize these two evaluation results.

Keywords: actively learning, art appreciation, EDA, Kinect V2

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Authors: Najith Duminda Galmangoda Guruge, Nadeeka Rathnayake, Vinodani Wimalasena, Dinesha Wijesooriya

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Investing in Early Learning can improve children’ interests for education and makes them ready for school. Children in economically disadvantaged communities may have reduced readiness for schools. Health Promotion approach enables communities including disadvantaged to control over their health. Mothers of children under the age five in ‘Alapathwewa’ community (n=40) were selected as the sample with the aim to promote early learning of children to improve their school readiness. Mothers in ‘Morakeewa’ community (n=40) were the control. Interventions were for a period of 2 years and children of these mothers were followed up to school entry. Importance of early learning and possibility of providing quality learning environments for children at a low cost was discussed with mothers in an experimental setting by facilitators. Mothers were enabled to make age-appropriate baby rooms which provide learning opportunities. Collective community playhouses and play areas were developed by mothers to provide opportunities for children to interact and learn with each other. Mothers started discussing with each other and sharing experiences. The progress was monitored by mothers at regular intervals. Data regarding school competencies of children were obtained from school teachers. School teachers measured thirteen competencies of children on a scale of ‘very good, good, moderate and weak’. All children in the experimental group were in ‘very good’ level in two competencies, ‘communicate friendly with others’ and ‘express ideas well’. Children in the experimental group reported a significantly higher achievement of all thirteen competencies (p < .05) than children in control. Providing quality early learning environments for children even in economically disadvantaged settings makes them ready for schools. Through a Health Promotion approach, early learning experiences for children can be provided at a low cost.

Keywords: disadvantaged, early learning, economically, health promotion

Procedia PDF Downloads 258

Authors: John Hardy

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Over the last decade, the world has witnessed an unprecedented rise in the quality and availability of violent extremist propaganda. This phenomenon has been fueled primarily by three interrelated trends: rapid adoption of online content mediums by creators of violent extremist propaganda, increasing sophistication of violent extremist content production, and greater coordination of content and action across violent extremist organizations. In particular, the self-styled ‘Islamic State’ attracted widespread attention from its supporters and detractors alike by mixing shocking video and imagery content in with substantive ideological and political content. Although this practice was widely condemned for its brutality, it proved to be effective at engaging with a variety of international audiences and encouraging potential supporters to seek further information. The reasons for the noteworthy success of this kind of shock-value propaganda content remain unclear, despite many governments’ attempts to produce counterpropaganda. This study examines violent extremist propaganda distributed by five terrorist organizations between 2010 and 2016, using material released by the ‎Al Hayat Media Center of the Islamic State, Boko Haram, Al Qaeda, Al Qaeda in the Arabian Peninsula, and Al Qaeda in the Islamic Maghreb. The time period covers all issues of the infamous publications Inspire and Dabiq, as well as the most shocking video content released by the Islamic State and its affiliates. The study uses frame analysis to distinguish thematic from symbolic content in violent extremist propaganda by contrasting the ways that substantive ideology issues were framed against the use of symbols and violence to garner attention and to stylize propaganda. The results demonstrate that thematic content focuses significantly on diagnostic frames, which explain violent extremist groups’ causes, and prognostic frames, which propose solutions to addressing or rectifying the cause shared by groups and their sympathizers. Conversely, symbolic violence is primarily stylistic and rarely linked to thematic issues or motivational framing. Frame analysis provides a useful preliminary tool in disentangling substantive ideological and political content from stylistic brutality in violent extremist propaganda. This provides governments and researchers a method for better understanding the framing and content used to design narratives and propaganda materials used to promote violent extremism around the world. Increased capacity to process and understand violent extremist narratives will further enable governments and non-governmental organizations to develop effective counternarratives which promote non-violent solutions to extremists’ grievances.

Keywords: countering violent extremism, counternarratives, frame analysis, propaganda, terrorism, violent extremism

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Authors: Jessica Chakowa

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Learning a foreign language requires practice that needs to be undertaken beyond the classroom. Nowadays, learners can find a lot of resources online, but it can be challenging for them to find suitable material, receive timely and effective feedback on their progress, and, more importantly practice the target language with native speakers. This paper focuses on the development of interactive activities combined with online tutoring sessions to consolidate and enhance the learning experience of beginner students of French at * University. This project is based on collaboration with four pre-service teachers from a French university. It calls for authentic language learning material, real-life situations, cultural awareness, and aims for the sustainability of learning and teaching. The paper will first present the design of the project as part of a holistic approach. It will then provide some examples of activities before commenting on the learners and the teachers’ experiences based on quantitative and qualitative data obtained through activity reports, surveys and focus groups. The main findings of the study lie in the tension between the willingness to achieve pedagogical goals and to be involved in authentic interactions, highlighting the complementary between the role of the learner and the role of teacher. The paper will conclude on benefits, challenges and recommendations when implementing such educational projects.

Keywords: authenticity, language teaching and learning, online interaction, sustainability

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Authors: Novia Dwi Prabandari, Diah Ayu Asmarani

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Soluble fiber can accelerate the metabolism of cholesterol. Pectin and gum has been used in the form of substance additive for material stabilizer and emulsifier. Pectin supplementation in laying hens can decimate the cholesterol content in egg yolk and muscle. Therefore, this laying hens’ feed is regular feed chickens enriched with soluble fiber (Pectin, Xanthan gum, and Guar gum) to produce eggs and muscle with lower cholesterol than usual.The ingredients are mixed in the ratio of concentrate 45%, corn flour 25%, soybean meal 20%, and extract of soluble fiber 10%. Once all the ingredients are mixed and then evaporated with temperature < 80 °C. Then put in the grinding machine resulting in a circular shape with holes 2-3 mm in diameter, after it dried up the water content in the feed is less than 14%. Eggs from laying hen with soluble fiber fortification feed intake will have lower cholesterol levels in eggs than regular feed. So even with the cholesterol content in the muscle, it is because chicken feed fortified with soluble fiber will accelerate the metabolism of cholesterol and cause cholesterol deposits in the chicken less. The use of this kind of laying hens feed is produce eggs with high protein content can be consumed more for people who have hypercholesterolemia.

Keywords: pectin, xanthan gum, guar gum, laying hen, cholesterol

Procedia PDF Downloads 444

Authors: Sebaa H., Cherifi F., Djabeur Abderrezak M.

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Argania spinosa, Sapotaceae sole representative in Algeria and Morocco; hence it is endemic in these regions. However, it is a recognised oil, forage, and timber tree highly adapted to aridity. The exploitation of the argan fruits produces considerable amounts of under or related products. These products, such as the endocarps of a fruit, recuperated after the use of kernels to extract oil. This research studies in detail the contents of total phenolic content was determined by Folin Ciocalteu reagent and Flavonoids by aluminum chloride colorimetric assay). Antioxidant activity of extracts was expressed as the percentage of DPPH radical inhibition and IC50 values (μg/mL). Antimicrobial activity evaluated using agar disk diffusion method against reference Pseudomonas aeruginosa ATTC 27453, Escherichia coli ATCC 23922. Immature endocarps showed a higher polyphenol content than mature endocarps. The total phenolic content in immature endocarps was found to vary from 983,75+ /- 0.45 to 980,1 +/- 0.43 mg gallic acid equivalents/g dry weight, whereas in mature endocarps, the polyphenol content ranged from 100,58 mg/g +/- 0.42 to 105 +/- 0.55% mg gallic acid equivalent / g dry weight. The flavonoid content was 16.5 mg equivalent catechin/g dry weight and 9.81mg equivalent catechin /g dry weight for immature and mature endocarp fruits, respectively. DPPH assay of the endocarps extract yielded a half-maximal effective concentration (IC50) value in the immature endocarps (549.33 μg/mL) than in mature endocarps (322 μg/mL). This result can be attributed to the higher phenolics and flavonoid compounds in the immature endocarps. Methanol extract of immature endocarps exhibited antibacterial activity against E.colie (inhibition zone, 11mm).

Keywords: antioxidant activity, antimicrobial activity, total phenolic content, DPPH assay

Procedia PDF Downloads 118

Authors: Muhammad Bilal, Adil Ahmed

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This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

Procedia PDF Downloads 117

Authors: Jacob Medupe

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Life as we know it has changed since the global outbreak of Coronavirus Disease 2019 (COVID-19) and business as usual will not continue. The human impact of the COVID-19 crisis is already immeasurable. Moreover, COVID-19 has already negatively impacted economies, livelihoods and disrupted food systems around the world. The disruptive nature of the Corona virus has affected every sphere of life including the culture and teaching and learning. Right now the majority of education research is based around classroom management techniques that are no longer necessary with digital delivery. Instead there is a great need for new data about how to make the best use of the one-on-one attention that is now becoming possible (Diamandis & Kotler, 2014). The COVID-19 pandemic has necessitated an environment where the South African learners are focused to adhere to social distancing in order to minimise the wild spread of the Corona virus. This arrangement forces the student to utilise the online classroom technologies to continue with the lessons. The historical reality is that the country has not made much strides on the closing of the digital divide and this is particularly a common status quo in the deep rural areas. This will prove to be a toll order for most of the learners affected by the Corona Virus to be able to have a seamless access to the online learning facilities. The paper will seek to look deeply into this reality and how the Corona virus has brought us to the reality that South Africa remains a deeply unequal society in every sphere of life. The study will also explore the state of readiness for education system around the online classroom environment.

Keywords: virtual learning, virtual classroom, COVID-19, Corona virus, internet connectivity, blended learning, online learning, distance education, e-learning, self-regulated Learning, pedagogy, digital literacy

Procedia PDF Downloads 127

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 137

Authors: Mariam Khomasuridze, Nino Chkhartishvili, Irma Chanturia

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The influence of preharvest and postharvest factors on resveratrol, myricetin and quercetin content of wine was studied during the experiment. The content of cis and trans resveratrol, myricetin and quercetin were analyzed by HPLC. In frame of experiment, the various factors affecting on wine composition were researched: variety, climate, viticulture practices, grape maturity, harvesting methods and wine making techniques. The results have shown that varietal potential and amount of yield play the most important role in formation of antioxidant compounds. Based on achieved results, the usage of medium roast oak chips protects resveratrol, myricetin, and quercetin from coagulation and precipitation. Compared to the control samples, the wines, produced by addition of oak chips were approximately four times richer with these antioxidant compounds. The retention of resveratrol was lowered with 45 % in wines, producing in Qvevri by Georgian traditional technology without controlling temperature during fermentation. The opposite effects in case of myricetin, quercetin and total phenolics content were determined. Their concentrations were higher with 56-78%, then in the fermented tank at 22 -25 °C. As the result of the experiment, the optimal technology scheme of wine was worked out, reached by biologically active compounds: resveratrol, myricetin, and quercetin.

Keywords: resveratrol, miricetin, quercetin, wine

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Authors: Bok Check Meng, Goh Ying Soon

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Giving additional learning materials such as Chinese fantasy novel to non-native learners can be strenuous. Instructors have to understand the underpinning theories about cognitive theory for new word instruction. This paper discusses the underpinning theories. Relevant literature reviews are given. There are basically five major areas of cognitive related theories mentioned in this article. These include motivational learning theory, Affective theory of learning, Cognitive psychology theory, Vocabulary acquisition theory and Bloom’s cognitive levels theory. A theoretical framework has been constructed. Thus, this will give a hand in ensuring non-native learners might gain positive outcomes in the instruction process. Instructors who are interested in teaching new word from Chinese fantasy novel in specific to support additional learning might be able to get insights from this article.

Keywords: Chinese fantasy novel, new word teaching, non-native learners, cognitive theory, bloom

Procedia PDF Downloads 735

Authors: Mohammad Yusuf, Qazi Fariduddin

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The main aim of this study was to explore the different cultivars of Vigna radiata on basis of photosynthesis, antioxidants and proline to assess Ni-sensitive and Ni-tolerant cultivar. Seeds of five different cultivars were sown in soil amended with different levels of Ni (0, 50, 100, or 150 mg kg 1). At 30 d stage, plants were harvested to assess the various parameters. The Ni treatment diminished growth, leaf water potential, chlorophyll content and net photosynthesis along with nitrate reductase and carbonic anhydrase activities in the concentration dependent manner whereas, it enhanced proline content and various antioxidant enzymes. The varieties T-44 found least affected, whereas PDM-139 experienced maximum damage at 150 mg kg-1 of Ni. Moreover, T-44 possessed maximum activity of antioxidant enzymes and proline content at all the levels of metal whereas PDM-139 possessed minimum values. Therefore, T-44 and PDM-139 were established as the most resistant and sensitive varieties, respectively.

Keywords: Vigna radiata, antioxidants, nickel, photosynthesis, proline

Procedia PDF Downloads 223

Authors: Xi Vivien Wu, Emily Neo Kim Ang, Yi Jung Tung, Wenru Wang

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Background and Objective: The increase in life expectancy and emphasis on self-reliance for the older adults are global phenomena. As such, lifelong learning in the community is considered a viable means of promoting successful and active aging. This systematic review aims to examine various lifelong learning programs for community-dwelling older adults and to synthesize the contents and outcomes of these lifelong learning programs. Methods: A systematic search was conducted in July to December 2016. Two reviewers were engaged in the process to ensure creditability of the selection process. Narrative description and analysis were applied with the support of a tabulation of key data including study design, interventions, and outcomes. Results: Eleven articles, which consisted of five randomized controlled trials and six quasi-experimental studies, were included in this review. Interventions included e-health literacy programs with the aid of computers and the Internet (n=4), computer and Internet training (n=3), physical fitness programs (n=2), music program (n=1), and intergenerational program (n=1). All studies used objective measurement tools to evaluate the outcomes of the study. Conclusion: The systematic review indicated lifelong learning programs resulted in positive outcomes in terms of physical health, mental health, social behavior, social support, self-efficacy and confidence in computer usage, and increased e-health literacy efficacy. However, the lifelong learning programs face challenges such as funding shortages, program cuts, and increasing costs. A comprehensive lifelong learning program could be developed to enhance the well-being of the older adults at a more holistic level. Empirical research can be done to explore the effectiveness of this comprehensive lifelong learning program.

Keywords: community-dwelling older adults, e-health literacy program, lifelong learning program, the wellbeing of the older adults

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Authors: Violina R. Angelova, Mariana N. Perifanova-Nemska, Galina P. Uzunova, Krasimir I. Ivanov, Huu Q. Lee

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A field study was conducted to evaluate the efficacy of the sunflower (Helianthus annuus L.) for phytoremediation of contaminated soils. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with a randomized, complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vemicompost amendments added at 20 and 40 t/daa) were carried out. The accumulation of heavy metals in the sunflower plant and the quality of the sunflower oil (heavy metals and fatty acid composition) were determined. The tested organic amendments significantly influenced the uptake of Pb, Zn and Cd by the sunflower plant. The incorporation of 40 t/decare of compost and 20 t/decare of vermicompost to the soil led to an increase in the ability of the sunflower to take up and accumulate Cd, Pb and Zn. Sunflower can be subjected to the accumulators of Pb, Zn and Cd and can be successfully used for phytoremediation of contaminated soils with heavy metals. The 40 t/daa compost treatment led to a decrease in heavy metal content in sunflower oil to below the regulated limits. Oil content and fatty acids composition were affected by compost and vermicompost amendment treatments. Adding compost and vermicompost increased the oil content in the seeds. Adding organic amendments increased the content of stearic, palmitoleic and oleic acids, and reduced the content of palmitic and gadoleic acids in sunflower oil. The possibility of further industrial processing of seeds to oil and use of the obtained oil will make sunflowers economically interesting crops for farmers of phytoremediation technology.

Keywords: heavy metals, phytoremediation, polluted soils, sunflower

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Authors: Nalini Chitanand

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Given the dynamic nature of the higher education landscape, induction programmes for new academics has become the norm nowadays to support academics negotiate these rough terrain. This study investigates an induction programme for new academics in a higher education institution to establish what difference it has made to participants. The findings revealed that the benefits ranged from creating safe spaces for collaboration and networking to fostering reflective practice and contributing to the scholarship of teaching and learning. The study also revealed that some of the intentions of the programme may not have been achieved, for example transformative learning. This led to questioning whether this intention is an appropriate one given the short duration of the programme and the long, drawn out process of transformation. It may be concluded that the academic induction programme in this study serves to sow the seeds for transformative learning through fostering critically reflective practice. Recommendations for further study could include long term impact of the programme on student learning and success, these being the core business of higher education. It is also recommended that in addition to an induction programme, the university invests in a mentoring programme for new staff and extend the support for academics in order to sustain critical reflection and which may contribute to transformative educational practice.

Keywords: induction programme, reflective practice, scholarship of teaching, transformative learning

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Authors: Ismail Halijah, Abdullah Rusli

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Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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Authors: Niphattha Hannapha

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This paper examines how the classroom environment influences slow learners’ learning achievement; it focuses on how seating patterns affect students’ behaviours and which patterns best contribute to students’ learning performance. The researcher studied how slow learners’ characteristics and seating patterns influenced their behaviours and performance at Ban Hin Lad School. As a nonparticipant observation, the target groups included 15 slow learners from Prathomsueksa (Grades) 4 and 5. Students’ behaviours were recorded during their learning activities in order to minimize their reading and written expression disorder in Thai language tutorials. The result showed four seating patterns and two behaviors which obstructed students’ learning. The average of both behaviours mostly occurred when students were seated with patterns 1 (the seat facing the door, with the corridor alongside) and 3 (the seat alongside the door, facing the aisle) respectively. Seating patterns 1 and 3 demonstrated visibility (the front and side) of a walking path with two-way movement. However, seating patterns 2 (seating with the door alongside and the aisle at the back) and 4 (sitting with the door at the back and the aisle alongside) demonstrated visibility (the side) of a walking path with one-way movement. In Summary, environmental design is important to enhance concentration in slow learners who have reading and writing disabilities. This study suggests that students should be seated where they can have the least visibility of movement to help them increase continuous learning. That means they can have a better chance of developing reading and writing abilities in comparison with other patterns of seating.

Keywords: slow learning, interior design, interior environment, classroom

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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The primary aim of the present study is to undertake an extensive comparative examination of distance learning and blended learning modalities, with a particular focus on assessing their efficacy during the period of confinement imposed by the COVID-19 pandemic. This investigation is grounded in the firsthand experiences of educators at the high school and secondary levels across both private and public educational institutions. To gather the necessary data, we designed and distributed a meticulously crafted survey to these educators, soliciting detailed accounts of their professional experiences throughout this challenging period. The survey's objectives include elucidating the specific difficulties faced by teachers, as well as highlighting the innovative pedagogical strategies they developed in response to these challenges. By synthesizing the insights gained from this survey, we aim to foster an exchange of experiences among educators and to generate informed recommendations that will guide future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

Procedia PDF Downloads 122

Authors: Dorottya Horváth, Tímea Harmath-Tánczos

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Attention deficit hyperactivity disorder (ADHD) and learning disabilities are common neurocognitive disorders that can have a significant impact on a child's academic performance. ADHD is characterized by inattention, hyperactivity, and impulsivity, while learning disabilities are characterized by difficulty with specific academic skills, such as reading, writing, or math. The aim of this study was to investigate the working memory, executive, and attention functions of neurotypical children and children with ADHD and learning disabilities in order to fill the gaps in the Hungarian mean test scores of these cognitive functions in children with neurocognitive disorders. Another aim was to specify the neuropsychological differential diagnostic toolkit in terms of the relationships and peculiarities between these cognitive functions. The research question addressed in this study was: How do the working memory, executive, and attention functions of neurotypical children compare to those of children with ADHD and learning disabilities? A self-administered test battery was used as a research tool. Working memory was measured with the Non-Word Repetition Test, the Listening Span Test, the Digit Span Test, and the Reverse Digit Span Test; executive function with the Letter Fluency, Semantic Fluency, and Verb Fluency Tests; and attentional concentration with the d2-R Test. The data for this study was collected from 115 children aged 9-14 years. The children were divided into three groups: neurotypical children (n = 44), children with ADHD without learning disabilities (n = 23), and children with ADHD with learning disabilities (n = 48). The data was analyzed using a variety of statistical methods, including t-tests, ANOVAs, and correlational analyses. The results showed that the performance of children with neurocognitive involvement in working memory, executive functions, and attention was significantly lower than the performance of neurotypical children. However, the results of children with ADHD and ADHD with learning disabilities did not show a significant difference. The findings of this study are important because they provide new insights into the cognitive profiles of children with ADHD and learning disabilities and suggest that working memory, executive functions, and attention are all impaired in children with neurocognitive involvement, regardless of whether they have ADHD or learning disabilities. This information can be used to develop more effective diagnostic and treatment strategies for these disorders.

Keywords: ADHD, attention functions, executive functions, learning disabilities, working memory

Procedia PDF Downloads 95

Authors: Ene Rosemary Ndidiamaka, Nwangwu Florence Chinyere

Abstract:

The physiochemical properties of the melon seed oil was studied to determine its potentials as viable feed stock for biodisel production. The melon seed was extracted by solvent extraction using n-hexane as the extracting solvent. In this research, methanol was the alcohol used in the production of biodiesel, although alcohols like ethanol, propanol may also be used. Sodium hydroxide was employed for the catalysis. The melon seed oil was characterized for specific gravity, pH, ash content, iodine value, acid value, saponification value, peroxide value, free fatty acid value, flash point, viscosity, and refractive index using standard methods. The melon seed oil had very high oil content. Specific gravity and flash point of the oil is satisfactory. However, moisture content of the oil exceeded the stipulated ASRTM standard for biodiesel production. The overall results indicates that the melon seed oil is suitable for single-stage transesterification process to biodiesel production.

Keywords: biodiesel, catalyst, melon seed, transesterification

Procedia PDF Downloads 368