Search results for: academic performance prediction

Authors: Dana Page, Erica McClure, Kate Snider, Jenni Pollard, Tim Landrum, Jeff Valentine

Abstract:

Extensive research has been conducted on students with emotional and behavioral disorders (EBD) and their rates of challenging behavior. In the past, however, less attention has been given to their academic achievement and outcomes. Recent research examining outcomes for students with EBD has indicated that these students receive lower grades, are less likely to pass classes, and experience higher rates of school dropout than students without disabilities and students with other high incidence disabilities. Given that between 2% and 20% of the school-age population is likely to have EBD (though many may not be identified as such), this is no small problem. Despite the need for increased examination of this population’s academic achievement, research on the actual performance of students with EBD has been minimal. This study reports the results of a meta-analysis of the limited research examining academic achievement of students with EBD, including effect sizes of assessment scores and discussion of moderators potentially impacting academic outcomes. Researchers conducted a thorough literature search to identify potentially relevant documents before screening studies for inclusion in the systematic review. Screening identified 35 studies that reported results of academic assessment scores for students with EBD. These studies were then coded to extract descriptive data across multiple domains, including placement of students, participant demographics, and academic assessment scores. Results indicated possible collinearity between EBD disability status and lower academic assessment scores, despite a lack of association between EBD eligibility and lower cognitive ability. Quantitative analysis of assessment results yielded effect sizes for academic achievement of student participants, indicating lower performance levels and potential moderators (e.g., race, socioeconomic status, and gender) impacting student academic performance. In addition to discussing results of the meta-analysis, implications and areas for future research, policy, and practice are discussed.

Keywords: students with emotional behavioral disorders, academic achievement, systematic review, meta-analysis

Procedia PDF Downloads 70

Authors: Maria Belen C. Costa, Liza C. Costa

Abstract:

Teachers have an important influence on students’ academic achievement. Teachers play a crucial role in educational attainment because they stand in the interface of the transmission of knowledge, values, and skills in the learning process through the instructional strategies they employ in the classroom. The level of achievement of students in school depends on the degree of effectiveness of instructional strategies used by the teacher. Thus, this study was conceptualized and conducted to examine the instructional strategies preferred and used by the Science and Mathematics teachers and the impact of those strategies in their teaching performance and students’ academic achievement in Science and Mathematics. The participants of the study comprised a total enumeration of 61 teachers who were chosen through total enumeration and 610 students who were selected using two-stage random sampling technique. The descriptive correlation design was used in this study with a self-made questionnaire as the main tool in the data gathering procedure. Relationship among variables was tested and analyzed using Spearman Rank Correlation Coefficient and Wilcoxon Signed Rank statistics. The teacher participants under study mainly belonged to the age group of ‘young’ (35 years and below) and most were females having ‘very much experienced’ (16 years and above) in teaching. Teaching performance was found to be ‘very satisfactory’ while academic achievement in Science and Mathematics was found to be ‘satisfactory’. Demographic profile and teaching performance of teacher participants were found to be ‘not significant’ to their instructional strategy preferences. Results implied that age, sex, level of education and length of service of the teachers does not affect their preference on a particular instructional strategy. However, the teacher participants’ extent of use of the different instructional strategies was found to be ‘significant’ to their teaching performance. The instructional strategies being used by the teachers were found to have a direct effect on their teaching performance. Academic achievement of student participants was found to be ‘significant’ to the teacher participants’ instructional strategy preferences. The preference of the teachers on instructional strategies had a significant effect on the students’ academic performance. On the other hand, teacher participants’ extent of use of instructional strategies was showed to be ‘not significant’ to the academic achievement of students in Science and Mathematics. The instructional strategy being used by the teachers did not affect the level of performance of students in Science and Mathematics. The results of the study revealed that there was a significant difference between the teacher participants’ preference of instructional strategy and the student participants’ instructional strategy preference as well as between teacher participants’ extent of use and student participants’ perceived level of use of the different instructional strategies. Findings found a discrepancy between the teaching strategy preferences of students and strategies implemented by teachers.

Keywords: academic achievement, extent of use, instructional strategy, preferences

Procedia PDF Downloads 313

Authors: D. I. George Amalarethinam, A. Emima

Abstract:

Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

Procedia PDF Downloads 118

Authors: Ramazan Hasanzadeh, Leyla Vatandoust

Abstract:

This study examined the efficacy of motivation management training for students’ academic achievement and self-concept. The pretest–posttest quasi-experimental study used a cluster random sampling method to select subjects for the experimental (20 subjects) and control (20 subjects) groups. posttest was conducted with both groups to determine the effect of the training. An academic achievement and academic self-concept questionnaire (grade point average requirement) was used for the pretest and posttest. The results showed that the motivation management training increased academic self-concept and academic achievement.

Keywords: motivation management, academic self-concept, academic achievement, students

Procedia PDF Downloads 261

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

Procedia PDF Downloads 357

Authors: Nooraisah Katmon, Hartini Jaafar, Hazianti Abdul Halim, Jessnor Elmy Mat Jizat

Abstract:

Our study empirically examines the effect of student activities on Facebook and religion on academic performance. We extend prior research in this area in a number of ways. First, given the paucity of the research in this area particularly from the Asian context, we provide the evidence from developing country like Malaysia. Second, our sample drawn from Sultan Idris Education University in Malaysia, where graduates from these universities are unique since they are expected to be able to work in both education and industry environment, and presumed to play significant roles in shaping the development of future student’s intellectual at the Malaysian secondary school and Malaysian economy in general. Third, we control for religiosity aspect when examining the association between Facebook and academic performance, something that has been predominantly neglected by the prior studies. Fourth, unlike prior studies that circulating around the Christian sphere in measuring religiosity, we provide evidence from the Islamic perspective where the act of worships and practices are much more comprehensive rather than the Christian counterparts. Fifth, we examine whether Facebook activities and religiosity are complementary or substitutive each other in improving student’s academic performance. Our sample comprise of 60 undergraduates. Our result exhibit that students with high number of friends on facebook and frequent engagement on facebook activities, such as sharing links, send message, posting photo, tagging video as well as spending long hours on facebook generally are associated with lower academic performance. Our results also reported that student’s engagement in religious activities promotes better academic performance. When we examine the potential interaction effect between facebook and religiosity, our result revealed that religiosity is effective in reducing student’s interest on facebook, hence lead to better academic achievement. In other words, religious student will be less interested in joining activities on facebook and make them more perform than their counterparts. Our findings from this study should be able to assist the university management in shaping university policies and curriculum to regulate and manage student’s activities in order to enhance overall student’s quality. Moreover, the findings from this study are also of use to the policy maker such as Malaysian Communication and Multimedia Commissions to regulate the policy on the student’s access and activities on facebook.

Keywords: facebook, religiosity, academic performance, effect of student activities

Procedia PDF Downloads 303

Authors: Mohammadreza Mohebbi, Masoumeh Sanagou

Abstract:

The ability to predict clinical outcomes is of great importance to physicians and clinicians. A number of different methods have been used in an effort to accurately predict these outcomes. These methods include the development of scoring systems based on multivariate statistical modelling, and models involving the use of classification and regression trees. The process usually consists of two consecutive phases, namely model development and external validation. The model development phase consists of building a multivariate model and evaluating its predictive performance by examining calibration and discrimination, and internal validation. External validation tests the predictive performance of a model by assessing its calibration and discrimination in different but plausibly related patients. A motivate example focuses on prediction modeling using a sample of patients undergone coronary artery bypass graft (CABG) has been used for illustrative purpose and a set of primary considerations for evaluating prediction model studies using specific quality indicators as criteria to help stakeholders evaluate the quality of a prediction model study has been proposed.

Keywords: clinical prediction models, clinical decision rule, prognosis, external validation, model calibration, biostatistics

Procedia PDF Downloads 298

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, random forest, molecular descriptors, maccs keys

Procedia PDF Downloads 48

Authors: Sohyoung Won, Heebal Kim, Dajeong Lim

Abstract:

Genomic prediction is an effective way to measure the abilities of livestock for breeding based on genomic estimated breeding values, statistically predicted values from genotype data using best linear unbiased prediction (BLUP). Using haplotypes, clusters of linked single nucleotide polymorphisms (SNPs), as markers instead of individual SNPs can improve the reliability of genomic prediction since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with markers is higher. To efficiently use haplotypes in genomic prediction, finding optimal ways to define haplotypes is needed. In this study, 770K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 2506 cattle. Haplotypes were first defined in three different ways using 770K SNP chip data: haplotypes were defined based on 1) length of haplotypes (bp), 2) the number of SNPs, and 3) k-medoids clustering by LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; in each method, haplotypes defined to have an average number of 5, 10, 20 or 50 SNPs were tested respectively. A modified GBLUP method using haplotype alleles as predictor variables was implemented for testing the prediction reliability of each haplotype set. Also, conventional genomic BLUP (GBLUP) method, which uses individual SNPs were tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight was used as the phenotype for testing. As a result, using haplotypes defined by all three methods showed increased reliability compared to conventional GBLUP. There were not many differences in the reliability between different haplotype defining methods. The reliability of genomic prediction was highest when the average number of SNPs per haplotype was 20 in all three methods, implying that haplotypes including around 20 SNPs can be optimal to use as markers for genomic prediction. When the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles. Using haplotype alleles for genomic prediction showed better performance, suggesting improved accuracy in genomic selection. The number of predictor variables was decreased when the LD-based method was used while all three haplotype defining methods showed similar performances. This suggests that defining haplotypes based on LD can reduce computational costs and allows efficient prediction. Finding optimal ways to define haplotypes and using the haplotype alleles as markers can provide improved performance and efficiency in genomic prediction.

Keywords: best linear unbiased predictor, genomic prediction, haplotype, linkage disequilibrium

Procedia PDF Downloads 141

Authors: Natalie Frandsen

Abstract:

Pursuing post-secondary education is a milestone for many Canadian youths. This transition involves many changes and opportunities for growth. However, this may also be a period where challenges arise. Perhaps not surprisingly, mental health challenges for post-secondary students are common. This poses difficulties for students and instructors. Common mental-health-related symptoms (e.g., low motivation, fatigue, inability to concentrate) can affect academic performance, and instructors may need to provide accommodations for these students without the necessary expertise. ‘Distance education’ has been growing and gaining momentum in Canada for three decades. As a consequence of the COVID-19 pandemic, post-secondary institutions have been required to deliver courses using ‘remote’ methods (i.e., various online delivery modalities). The learning challenges and subsequent academic performance issues experienced by students with mental-health-related disabilities studying online are not well understood. However, we can postulate potential factors drawing from learning theories, the relationship between mental-health-related symptoms and academic performance, and learning design. Identifying barriers and opportunities to academic performance is an essential step in ensuring that students with mental-health-related disabilities are able to achieve their academic goals. Completing post-secondary education provides graduates with more employment opportunities. It is imperative that our post-secondary institutions take a holistic view of learning by providing learning and mental health support while reducing structural barriers. Health-promoting universities and colleges infuse health into their daily operations and academic mandates. Acknowledged in this Charter is the notion that all sectors must take an active role in favour of health, social justice, and equity for all. Drawing from mental health promotion and Universal Design for Learning (UDL) frameworks, relevant adult learning concepts, and critical digital pedagogy, considerations for mental-health-promoting, online learning community development will be summarized. The education sector has the opportunity to create and foster equitable and mental health-promoting learning environments. This is of particular importance during a global pandemic when the mental health of students is being disproportionately impacted.

Keywords: academic performance, community, mental health promotion, online learning

Procedia PDF Downloads 136

Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

Abstract:

Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

Procedia PDF Downloads 122

Authors: Endah Mastuti, Prihastuti Sudaryono

Abstract:

The rapid development of Internet usage and technology influences the academic behavior of students in high schools. One of the consequences is the emergence of academic procrastination behavior. Academic procrastination behavior is students’ procrastinate behavior in completing assignments. This study aimed to see whether there are differences in the duration of using the internet with academic procrastinate behavior among high school students in Surabaya. The number of research subject is 498 high school students. Instruments of the research are academic procrastination scale and duration of the internet usage questionnaire. The results from One Way Anova shows F value 0.241 with a significance level of 0.868 This demonstrates that there is no difference between the duration of the use of the Internet with academic procrastination behavior in high school students.

Keywords: academic procrastination, duration of internet usage, students, senior high school

Procedia PDF Downloads 361

Authors: Seun Mayowa Sunday

Abstract:

Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

Procedia PDF Downloads 137

Authors: Veena Rani

Abstract:

This paper presents the role of academic library in information literacy in the present time. Information is the very important aspect for the growth of any country. In this context information literacy is an essential tool in the development of various fields. Academic library is an essential part of university as well as of an institution. In Academic library we can include university library, college library as well as school library. Academic libraries are playing an important role for information literacy. Academic libraries provide excellent services for the benefit of students, teachers, researchers, and all those who are interested in education. All over the world many of the schemes, policies and services provide for information literacy.

Keywords: information literacy, academic library, tool literacy, higher education

Procedia PDF Downloads 373

Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

Procedia PDF Downloads 293

Authors: Qian Mao, Xiaozan Wang, Jiarong Zhong, Xiaolin Zou

Abstract:

Introduction: As a result of the decline of students' physical health level and the increase of study pressure, students’ academic performance is not so good. Objective: This study aims to verify whether the Brain-Break intervention in the fourth-grade classroom of primary school can improve students' physical health and academic performance. Methods: According to the principle of no difference in pre-test data, students from two classes of grade four in Fuhai Road Primary School, Fushan district, Yantai city, Shandong province, were selected as experimental subjects, including 50 students in the experimental class (25 males and 25 females) and 50 students in the control class (24 males and 26 females). The content of the experiment was that the students were asked to perform a 4-minute Brain-Berak program designed by the researcher in the second class in the morning and the afternoon, and the intervention lasted for 12 weeks. In addition, the lung capacity, 50-meter run, sitting body forward bend, one-minute jumping rope and one-minute sit-ups stipulated in the national standards for physical fitness of students (revised in 2014) were selected as the indicators of physical health. The scores of Chinese, Mathematics, and English in the unified academic test of the municipal education bureau were selected as the indicators of academic performance. The independent-sample t-test was used to compare and analyze the data of each index between the two classes. The paired-sample t-test was used to compare and analyze the data of each index in the two classes. This paper presents only results with significant differences. Results: in terms of physical health, lung capacity (P=0.002, T= -2.254), one-minute rope skipping (P=0.000, T=3.043), and one-minute sit-ups (P=0.045, T=6.153) were significantly different between the experimental class and the control class. In terms of academic performance, there is a significant difference between the Chinese performance of the experimental class and the control class (P=0.009, T=4.833). Conclusion: Adding Brain-Berak intervention in the classroom can effectively improve the cardiorespiratory endurance (lung capacity), coordination (jumping rope), and abdominal strength (sit-ups) of fourth-grade students. At the same time, it can also effectively improve their Chinese performance. Therefore, it is suggested to promote micro-sports in the classroom of primary schools throughout the country so as to help students improve their physical health and academic performance.

Keywords: academic performance, brain break, fourth grade, physical health

Procedia PDF Downloads 101

Authors: Abubakar Abdulkareem, Nasir Haruna Soba

Abstract:

This study investigates the non-utilization of AI tools for research and academic writing among academic staff in Nigerian universities using the perceived attribute of innovation theory by Rogers as a theoretical framework to guide the investigation. This study was framed in an interpretative research paradigm. A qualitative methodology and case study research design was adopted. Interviews were conducted with 20 academic staff. The study used a thematic analysis process to identify 115 narratives. The narratives are organized into five major categories and further collapsed into five theoretical constructs explaining the non-use of AI tools for research and academic writing. Findings from this study revealed some of the reasons for the non-utilization of AI tools for research and academic writing as lack of Awareness, perceived Complexity, trust and Reliability Concerns, cost and accessibility, ethical and Privacy concerns and, cultural and institutional factors, etc.

Keywords: non-utilization, AI tools, research and academic writing, academic staff

Procedia PDF Downloads 51

Authors: Adam Marks, Munir Majdalawieh, Maytha Al Ali

Abstract:

While research is rich with what criteria could be included in the academic program review processes, there is rarely any mention of how this significant and complex process should be managed. This paper proposes using project management methodology in alignment with the program review criteria of the Dickeson’s Prioritizing Academic Programs model. Project management and academic program review share two distinct characteristics; one is their life cycle, and the second is the core knowledge areas they use. This aligned and structured approach offers academic administrators a step-by-step guide that can help them manage this process and effectively assess academic programs.

Keywords: project management, academic program, program review, education, higher education institution, strategic management

Procedia PDF Downloads 368

Authors: Caroline Nnokwe, Iheanyi Eneremadu

Abstract:

Teachers and principals are vital and integral parts of the educational system. For educational objectives to be met, the role of teachers and the functions of the principals are not to be overlooked. However, the inability of teachers and principals to carry out their roles effectively has impacted the outcome of the students’ performance. The study, therefore, examined teachers’ roles and principal’s administrative functions as correlates of effective academic performance of public secondary school students in Imo state, Nigeria. Four research questions and two hypotheses guided the study. The study adopted a correlation research design. The sample size was 5,438 respondents via the Yaro-Yamane technique, which consists of 175 teachers, 13 principals and 5,250 students using the proportional stratified random sampling technique. The instruments for data collection were a researcher-made questionnaire titled Teachers’ Role/Principals’ Administrative Functions Questionnaire (TRPAFQ) with a Cronbach Alpha coefficient of .82 and student's internal results obtained from the school authorities. Data collected were analyzed using the Pearson product-moment correlation coefficient and simple linear regression. Research questions were answered using Pearson Product Moment Correlation statistics, while the hypotheses were tested at 0.05 level of significance using regression analysis. The findings of the study showed that the educational qualification of teachers, organizing, and planning correlated student’s academic performance to a great extent, while availability and proper use of instructional materials by teachers correlated the academic performance of students to a very high extent. The findings also revealed that there is a significant relationship between teachers’ role, principals’ administrative functions and student’s academic performance of public secondary schools in Imo State, The study recommended among others that there is the need for government, through the ministry of education, and education authorities to adequately staff their supervisory department in order to carry out proper supervision of secondary school teachers, and also provide adequate instructional materials to ensure greater academic performance among secondary school students of Imo state, Nigeria.

Keywords: instructional materials, principals’ administrative functions, students’ academic performance, teacher role

Procedia PDF Downloads 87

Authors: Dominic Winston Kaku

Abstract:

The academic performance of students is an area of great concern in education to the various stakeholders of education. This is because the academic performance of students is widely used as a measure of the success of the educational process. There are several factors, such as school-related factors, teachers related factors, pupils or students’ factors, and many others determining their academic performance. It appears that the management role of head teachers as a determining factor of pupils’ academic achievement is not much investigated. The management role of head teachers is an essential element in the educational process that has a huge influence on students’ academic performance. The aim of the research was to examine the management role of head teachers in improving the academic performance of students. The study employed a descriptive survey and was conducted among Junior High Schools in the Ellembelle District of the Western Region of Ghana. The respondents for the study were mainly all the head teachers, teachers, and some selected basic school pupils (JHS) in four-selected public basic schools in the Ellembelle district in the Western part of Ghana. A questionnaire was used to collect primary data from a sampling size of 252 persons, including 226 JHS pupils, all JHS teachers, and head teachers of all four selected schools. Descriptive statistics, specifically frequencies, percentages, pie charts, bar charts, means, and standard deviation, were used to analyse the data, and that formed the basis of the presentation of findings. The study discovered that planning academic activities, fostering relationships between the school and the community, supervising lessons, staff motivation, and punishing students who go wrong are some of the activities the head teachers participate in to help improve students’ academic performance. The academic performance of students is an area of great concern in education to the various stakeholders of education. This is because the academic performance of students is widely used as a measure of the success of the educational process. There are several factors, such as school-related factors, teachers related factors, pupils or students’ factors, and many others determining their academic performance. It appears that the management role of head teachers as a determining factor of pupils’ academic achievement is not much investigated. The management role of head teachers is an essential element in the educational process that has a huge influence on students’ academic performance. The aim of the research was to examine the management role of head teachers in improving the academic performance of students. The study employed a descriptive survey and was conducted among Junior High Schools in the Ellembelle District of the Western Region of Ghana. The respondents for the study were mainly all the head teachers, teachers, and some selected basic school pupils (JHS) in four-selected public basic schools in the Ellembelle district in the Western part of Ghana. A questionnaire was used to collect primary data from a sampling size of 252 persons, including 226 JHS pupils, all JHS teachers, and head teachers of all four selected schools. Descriptive statistics, specifically frequencies, percentages, pie charts, bar charts, means, and standard deviation, were used to analyse the data, and that formed the basis of the presentation of findings. The study discovered that planning academic activities, fostering relationships between the school and the community, supervising lessons, staff motivation, and punishing students who go wrong are some of the activities the head teachers participate in to help improve students’ academic performance.

Keywords: supervision, head teacher, academic performance, planning, motivation, relationships

Procedia PDF Downloads 66

Authors: Violetta Parutis

Abstract:

This qualitative study aims to answer the following research questions: i) What are the factors that students perceive as relevant to a) promoting and b) preventing good grades? ii) How does socio-economic status (SES) feature in those beliefs? We conducted in-depth interviews with 19 first- and second-year undergraduates of varying SES at a research-intensive university in the UK. The interviews yielded eight factors that students perceived as promoting and six perceived as preventing good grades. The findings suggested one significant difference between the beliefs of low and high SES students in that low SES students perceive themselves to be at a greater disadvantage to their peers while high SES students do not have such beliefs. This could have knock-on effects on their performance.

Keywords: social class, education, academic performance, students’ beliefs

Procedia PDF Downloads 179

Authors: B. O. Diyaolu

Abstract:

The web created by sport in academics has made it difficult for it to be separated from adolescent educational development. The enthusiasm expressed towards sport by students in higher institutions is quite enormous. Primarily, academic performance should be the pride of all students but whether sports affect the academic performance of student-athletes remain an unknown fact. This study investigated the influence of sports participation on academic performance among Afe Babalola University student-athletes. Ex post facto research design was used. Two groups of students were used for the study; Student-athlete (SA) and Regular Students (RS). Purposive sampling technique was used to select 224 student-athletes, only those that are regular in the university sports team training were considered and their records (i.e. name, department, level, matriculation number, and phone number) were collected through the assistance of their coaches. For the regular students, purposive sampling technique was used to select 224 participants, only those that have no interest in sports were considered and their records were retrieved from the college registration officer. The first and second semester examination results of the two groups were compared in 10 general study courses without their knowledge, using descriptive statistics of frequency counts, mean, and standard deviation. Out of the 10 compared courses, 7 courses result showed no significant difference between students-athlete and regular students while student-athletes perform better in 3 practically oriented courses. Sports role in academics is quite significant. Exposure to sports can help build the confidence that athletes need especially when it comes to practical courses. Student-athletes can perform better in academics if the environment is friendly and not intimidating. Lecturers and coaches need to work together in order to build a well cultured and intelligent graduate.

Keywords: academic performance, regular students, sports participation, student-athlete, university sports team

Procedia PDF Downloads 159

Authors: Yayra Dzakadzie

Abstract:

The descriptive cross-sectional survey study assessed dishonest academic intention, mediating academic goals, and attitude relationship with academic dishonesty among university undergraduate students in Ghana. The target population for this study was all the final-year undergraduate students enrolled full-time in Ghanaian public universities. One thousand two hundred (1,200) undergraduate students participated in the study. Multistage sampling was used to select the sample for the study. A structured questionnaire was used to collect the needed data to test hypotheses. Structural Equation Modelling (PLS-SEM) was used for the analyses. The results revealed that academic goals and attitudes had direct and indirect effects on academic dishonesty behaviour. Also, academic intention was statistically a significant mediator in the relationship that academic goals and attitude have with academic dishonesty. It was concluded that when academic goals are high, it compels individual students to try new strategies, and when academic goals are low, the students would like to “cut corners” to meet expectations. It was also concluded that when the attitude towards academic dishonesty is low, students are more unlikely to form an intention to be academically dishonest. It is recommended that lecturers should make their students aware of the goals that need to be attained in their courses and provide them with feedback on goal progress. Students should set their proximal goals and enhance their commitment so that they avoid putting things off. Enforcement of rules and regulations against academic dishonesty must be fully adhered to since students’ positive attitudes can result in high intention, which would lead to academic dishonesty behaviour.

Keywords: intention, academic goals, attitude, academic dishonesty, public university

Procedia PDF Downloads 100

Authors: L. N. P. Wedikandage, Mohamed Razmi Zahir

Abstract:

Technology is a global imperative because of its contributions to human existence and because it has improved global socioeconomic relations. As a result, the mobile phone has become the most important mode of communication today. Smartphones, Internet-enabled devices with built-in computer software and applications, are one of the most significant inventions of the twenty-first century. Technology is advantageous to many people, especially those involved in education. It is an important learning tool for today's schoolchildren. It enables students to access online learning platforms and course resources and interact digitally. Senior secondary students, in particular, have some of the most expensive and sophisticated mobile phones, tablets, and iPads capable of connecting to the internet and various social media platforms, other websites, and so on. At present, the use of mobile phones' potential for effective teaching and learning is growing. This is due to the benefits of mobile learning, including the ability to share knowledge without any limits in space or Time and the capacity to facilitate the development of critical thinking, participatory learning, problem-solving, and the development of lifelong communication skills. However, it is yet unclear how mobile devices may affect education and how they may affect opportunities for learning. As a result, the purpose of this research was to ascertain the relationship between mobile phone usage and the academic Performance of secondary-level students at an international school in Sri Lanka. The study's sample consisted of 523 secondary-level students from an international school, ranging from Form 1 to Upper 6. For the study, a survey research design and questionnaires were used. Google Forms was used to create the students' survey. There were three hypotheses tested to find out the relationship between mobile phone usage and academic preference. The findings show that there is a positive relationship between mobile phone usage and academic performance among secondary school students (the number of students obtaining simple passes is significantly higher when mobile phones are being used for more than 7 hours), no relationship between mobile phone usage and academic performance among secondary school students of different parents' occupations, and a relationship between the frequency of mobile phone usage and academic performance among secondary school students.

Keywords: mobile phone, academic performance, secondary level, international schools

Procedia PDF Downloads 87

Authors: Behzad Behnia, Noah LaRussa-Trott

Abstract:

In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

Procedia PDF Downloads 142

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

Abstract:

The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

Procedia PDF Downloads 262

Authors: Sobhy Fathy A. Hashesh

Abstract:

This study aimed at investigating the effect of Andalus Knowledge Phases and Times (ANPT) model of learning and the effect of 'Intel Education Contribution in ANPT' on the development of students’ academic performance and emotional quotient. The society of the study composed of Andalus Private Schools, elementary school students (N=700), while the sample of the study composed of four randomly assigned groups (N=80) with one experimental group and one control group to study "ANPT" effect and the "Intel Contribution in ANPT" effect respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to answer the study questions. Results of the study revealed that there were significant statistical differences between students’ academic performances and emotional quotients for the favor of the experimental groups. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: Al Andalus, emotional quotient, students, academic performance development

Procedia PDF Downloads 239

Authors: Afaf Alhusayni, Elizabeth Sheppard, Asiyya Jaffrani, Peter Mitchell, Lauren Marsh

Abstract:

Introduction: Previous research has found that people make systematic judgments about others based on small glimpses of their behavior. Furthermore, autistic people are consistently judged more negatively than non-autistic people in terms of favourability and approachability. Objectives: This project focuses on a hitherto unstudied type of judgment that is highly relevant within a university context, judgments about academic performance. This is particularly important as autistic university students are less likely to complete their degrees than neurotypical students. Methods: Twenty-five neurotypical perceivers (21 females - 4 males) viewed a series of 4s video clips featuring an individual ‘target’ displaying natural behavior. Nine of these targets were autistic and nine were neurotypical. Perceivers were asked to rate each target on four aspects related to university life (motivation, success, grades, and happiness). Results: Autistic targets were judged more negatively on all aspects compared to neurotypical targets. Conclusions: This study concludes that neurotypical perceivers negatively judge the academic performance of autistic students. This suggests that autistic university students face unfavorable scrutiny and judgment, which may negatively impact their academic success. Implications: These initial findings provide important evidence that autistic people are negatively stigmatized within education environments. Further work is needed to ascertain the extent to which these negative judgments may feed into attainment gaps for autistic students. This information is useful for the education department, government, and social care organizations, enabling change in the provision of support for autistic students.

Keywords: autistic person perception, academic performance, stigma and judgment, higher education

Procedia PDF Downloads 137

Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

Abstract:

Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

Procedia PDF Downloads 430

Authors: Junyu Chen, Peng Xu

Abstract:

In the context of global efforts to enhance building energy efficiency, accurate thermal load forecasting is crucial for both device sizing and predictive control. Variable Refrigerant Flow (VRF) systems are widely used in buildings around the world, yet VRF zonal load prediction has received limited attention. Due to differences between VRF zones in building-level prediction methods, zone-level load forecasting could significantly enhance accuracy. Given that modern VRF systems generate high-quality data, this paper introduces transfer learning to leverage this data and further improve prediction performance. This framework also addresses the challenge of predicting load for building zones with no historical data, offering greater accuracy and usability compared to pure white-box models. The study first establishes an initial variable set of VRF zonal building loads and generates a foundational white-box database using EnergyPlus. Key variables for VRF zonal loads are identified using methods including SRRC, PRCC, and Random Forest. XGBoost and LSTM are employed to generate pre-trained black-box models based on the white-box database. Finally, real-world data is incorporated into the pre-trained model using transfer learning to enhance its performance in operational buildings. In this paper, zone-level load prediction was integrated with transfer learning, and a framework was proposed to improve the accuracy and applicability of VRF zonal load prediction.

Keywords: zonal load prediction, variable refrigerant flow (VRF) system, transfer learning, energyplus

Procedia PDF Downloads 29