Parallel Method Research Articles

An AI-based fault detection and classification method for hybrid parallel HVAC/HVDC overhead transmission lines

In this paper, a novel method is presented to detect and classify the AC, DC, and AC/DC intersystem faults in hybrid parallel HVAC/HVDC overhead transmission lines (HPOTLs) on the same tower. In HPOTLs lines the presence of electromagnetic coupling between the AC and DC conductors induces components in the AC and DC lines which can affect the performance of their protection systems. To tackle these challenges, a protection method based on the decision tree (DT) algorithm and a fault energy index (FEI) is proposed for HPOTLs. The proposed method uses the sending-end voltages and currents of the AC and DC lines and some transformations to calculate the FEIs. The fault detection and classification algorithms and their criteria are derived by the DT algorithm. PSCAD and MATLAB software are used for HPOTL modeling, and voltage and current signals processing, respectively. Simulation results show that the proposed protection method can detect and classify different faults (AC and DC line faults and AC/DC intersystem faults) accurately, and is able to discriminate between transmission line internal and external faults. Simplicity, high speed and accuracy, robustness to the fault resistance and noise, and not needing a telecommunication channel are important features of the proposed method.

Helping Others Facilitates Well-Being for Indigenous Peoples Living With HIV/AIDS in Canada.

Research has found that helping others facilitates well-being for Indigenous peoples living with HIV and AIDS, but limited research exists that investigates the mechanism(s) underlying this relationship. Indigenous perspectives posit that helping others facilitates well-being through the development of an individual's spiritual, physical, emotional, and mental aspects (four aspects). Similarly, self-determination theory posits that helping others facilitates well-being by satisfying basic psychological needs. In the present study, we examined if helping others facilitates well-being through the fulfillment of the spiritual, physical, emotional, and mental aspects among Indigenous peoples living with HIV and AIDS. We used a convergent parallel mixed methods design, coupled with a community-engaged approach grounded in the United Nations Greater Involvement of People Living with HIV and AIDS principles and Indigenous and decolonizing research methodologies. Survey (n = 117) and interview data (n = 9) collected by an Indigenous-led HIV/AIDS organization in Canada were employed to examine the relationship between helping, the four aspects, and well-being. Participants were primarily First Nations leaders and mentors who live with HIV/AIDS, with some Métis and Inuit. A parallel multiple mediation model and reflexive thematic analysis were used to analyze the relationship between helping, the four aspects, and well-being. Mixed-methods findings support the idea that helping others promotes well-being by fulfilling the emotional and mental aspects. Qualitative findings demonstrated this relationship for all four aspects. This research may facilitate the development of programs to support Indigenous peoples living with HIV/AIDS well-being and contribute to the literature on integrating Indigenous perspectives and methodologies within psychological research.

Fostering TBL Success at Alfaisal University: A Complex Adaptive Systems Approach.

This study explores the implementation of Team-Based Learning (TBL) at Alfaisal University's College of Medicine through the lens of Complex Adaptive Systems (CAS) theory. The research question investigates how the application of CAS principles can enhance the implementation and effectiveness of TBL in medical education. The study employed a convergent parallel mixed methods longitudinal design, integrating quantitative performance metrics and qualitative themes. Quantitative analysis revealed modest improvements in individual and team-based learning scores, with a promising trend of students moving from the lower to the higher quartiles over time. Qualitative insights aligned with CAS principles, highlighting the adaptive implementation, emergent outcomes, self-organization, positive feedback loops, and depth of learning facilitated by TBL. The findings demonstrate the value of a CAS-informed approach in navigating the complexities of educational change and fostering a more resilient and adaptive educational model. The study contributes to the understanding of how CAS theory can guide the successful implementation of innovative pedagogies like TBL in medical education.

A Preliminary Sentiment Analysis on Digital Barriers among Senior Citizens During Covid-19 Pandemic

Nowadays, digital technology has been an important element in assisting the community in their daily routine. During the COVID-19 era, The Special Committee for Ensuring Access to COVID-19 Vaccine Supply (JKJAV) has been initiated to assist the health and well-being of Malaysian citizens in recovering from the COVID-19 pandemic. MySejahtera, a healthcare application technology, has been used by Malaysian citizens for seeking vaccination information as well as updating their health status. While there are benefits to using the application, there is still a challenge in using the technology among senior citizens. This study aims to investigate digital barriers to using a healthcare application, known as MySejahtera, among senior citizens in Kelantan. This study also reveals lessons learned regarding the use of technology among senior citizens during the Covid-19 era. Convergent parallel mixed method research design is initiated to produce a sentiment analysis for identifying digital barriers issues and challenges among senior citizens in Kelantan. 5 respondents aged from 60 to 80 years old were interviewed to obtain their sentiments on using digital technology for vaccination information and Covid-19 news. This study highlights issues namely awareness of knowledge, misconception about digital technology, information quality and technology usage among the senior citizens in Kelantan. This study summarizes that there is a need to reduce digital barriers among senior citizens to ensure digital inclusion for their benefit in health and well-being.

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

In recent years, the need for high-performance computing solutions has increased due to the growing complexity of computational tasks. The use of parallel processing techniques has become essential to address this demand. In this study, an Open Computing Language (OpenCL)-based parallelization algorithm is implemented for the Constant Neighbors (CNe) and CNe with Predictor–Corrector (CpC) numerical methods, which are recently developed explicit and stable numerical algorithms to solve the heat conduction equation. The CPU time and error rate performance of these two methods are compared with the sequential implementation and Euler’s explicit method. The results demonstrate that the parallel version’s CPU time remains nearly constant under the examined circumstances, regardless of the number of spatial mesh points. This leads to a remarkable speed advantage over the sequential version for larger data point counts. Furthermore, the impact of the number of timesteps on the crossover point where the parallel version becomes faster than the sequential one is investigated.

A Long-Term Target Search Method for Unmanned Aerial Vehicles Based on Reinforcement Learning

Unmanned aerial vehicles (UAVs) are increasingly being employed in search operations. Deep reinforcement learning (DRL), owing to its robust self-learning and adaptive capabilities, has been extensively applied to drone search tasks. However, traditional DRL approaches often suffer from long training times, especially in long-term search missions for UAVs, where the interaction cycles between the agent and the environment are extended. This paper addresses this critical issue by introducing a novel method—temporally asynchronous grouped environment reinforcement learning (TAGRL). Our key innovation lies in recognizing that as the number of training environments increases, agents can learn knowledge from discontinuous trajectories. This insight leads to the design of grouped environments, allowing agents to explore only a limited number of steps within each interaction cycle rather than completing full sequences. Consequently, TAGRL demonstrates faster learning speeds and lower memory consumption compared to existing parallel environment learning methods. The results indicate that this framework enhances the efficiency of UAV search tasks, paving the way for more scalable and effective applications of RL in complex scenarios.

Multi-threaded parallel tetrahedral mesh improvement by combining atomic operation and graph coloring

In industrial numerical simulations, efficiently generating high-quality tetrahedral meshes remains a significant challenge. Advances in high-performance computing have made parallelization a practical approach to improving the quality of large-scale tetrahedral meshes. This study proposes a fine-grained multithreaded parallel method to accelerate tetrahedral mesh improvement. By utilizing atomic operations, we fundamentally address thread safety concerns. Additionally, through the precise use of atomic operations, task decomposition strategies, and a multithreaded memory model, we minimize the probability of task overlap and data races, thereby enhancing overall parallel mesh improvement efficiency. Experimental results demonstrate that our parallel mesh improver is robust and effective for complex industrial models. On a laptop with 16 threads, we achieved a tenfold increase in tetrahedral mesh improvement speed, with the quality of the improved meshes being comparable to that of the sequential process.

RegulEm, an unified protocol based-app for the treatment of emotional disorders: a parallel mixed methods usability and quality study

BackgroundInterest in mental health smartphone applications has grown in recent years. Despite their effectiveness and advantages, special attention needs to be paid to two aspects to ensure app engagement: to include patients and professionals in their design and to guarantee their usability. The aim of this study was to analyse the perceived usability and quality of the preliminary version of RegulEm, an app based in the Unified Protocol, as part of the second stage of the app development.MethodsA parallel mixed methods study was used with 7 professionals and 4 users who were previously involved in the first stage of the development of the app. MARS, uMARS and SUS scales were used, and two focus groups were conducted. Descriptive statistical analysis and a thematic content analysis were performed in order to gather as much information as possible on RegulEm’s usability and quality as well as suggestions for improvement.ResultsRegulEm’s usability was perceived through the SUS scale scores as good by users (75 points) and excellent by professionals (84.64 points), while its quality was perceived through the uMARS and MARS scales as good by both groups, with 4 and 4.14 points out of 5. Different areas regarding RegulEm’s usability and suggestions for improvement were identified in both focus groups and 20% of the suggestions proposed were implemented in the refined version of RegulEm.ConclusionRegulEm’s usability and quality were perceived as good by users and professionals and different identified areas have contributed to its refinement. This study provides a more complete picture of RegulEm’s usability and quality prior analysing its effectiveness, implementation and cost-effectiveness in Spanish public mental health units.

G protein coupled receptor transcripts in human immune cells and platelets.

G-protein coupled receptors (GPCRs) are encoded by nonabundant mRNAs, and it is difficult to detect them reliably with the highly parallel methods that are in general use. Because of this, we developed and validated a sensitive, specific, semi-quantitative method for detecting these transcripts. We have used the method to profile GPCR transcripts in white blood cells (WBCs)-B, CD4, CD8, NK, and dendritic cells; monocytes, and macrophage-like monocytes treated with granulocyte-macrophage colony-stimulating factor-as well as platelets. On average, the white cells studied expressed 160 receptor mRNAs (range, 123-206). Platelets made 69. Some, but far from all, of the receptors we found have been detected earlier. We believe our data should stimulate studies of receptor function and contribute to drug development.

Deep learning and feature reconstruction assisted vis-NIR calibration method for on-line monitoring of key growth indicators during kombucha production

Artificial intelligence (AI) technology is advancing the digitization and intelligence development of the food industry. A promising application is using deep learning-assisted visible near-infrared (vis-NIR) spectroscopy to monitor residual sugar and bacterial concentration in real-time, ensuring kombucha quality during production. The feature fingerprints of residual sugar and bacterial concentration were extracted by four variable selection algorithms and then reconstructed using serial and parallel processing methods. Based on these reconstructed features, Partial Least Squares (PLS) and Convolutional Neural Networks (1DCNN and 2DCNN) models were developed and compared. The experimental results showed that the 2DCNN model based on reconstruction features achieved superior performance. The RPDs of the residual sugar and bacterial concentrations models were 4.49 and 6.88, while the MAEs were 0.42 mg/mL and 0.04 (Abs), respectively. These results suggest that the proposed modeling strategy effectively supports quality control during kombucha production and provides a new perspective for spectral analysis.

Use of Natural Areas among Latinxs Living in South Carolina

The Latinx population in the United States (US) is growing. While Latinxs have historically been present in US cities and southwestern states, there is a notable surge in migration to new destination states, including South Carolina (SC). As the Latinx population grows and extends to new geographies, there is a need to examine the evolution of Latinxs’ outdoor recreation patterns. Exploring their changing preferences regarding public spaces can inform park management planning and policy. This study examines outdoor recreation use among SC-based Latinxs, exploring three central questions: 1. What are the outdoor recreation preferences among Latinxs living in SC? 2. What constraints do Latinxs face while engaging in outdoor recreation? 3. What are Latinxs’ primary motivations in visiting natural areas? This study employs a convergent parallel mixed method design. The quantitative phase consists of a cross-sectional sampling approach via online surveys, while the qualitative phase utilizes focus groups. Analyses of survey results include descrip-tive statistics and ANOVA and Chi-square tests for select variables. Qualitative analyses are based on a priori open coding with thematic development. Quantitative and qualitative data were first examined separately and later compared. Results suggest that walking/hiking is the primary outdoor recreation activity in which Latinxs engage. Focus-group participants also mentioned a variety of land- and water-based outdoor recreation activities. The most prevalent motivations for recreation experiences included relaxation, escape, and improved health. The top five factors preventing survey respondents from visiting natural areas were tiredness after work, insufficient time off work, insufficient time and money to visit natural areas, and proximity to natural areas. Focus group participants also reported various constraints hindering their visits to natural areas, including time, cost, safety, inadequate on-site amenities, weather, and Latinx-specific constraints. The findings indicate that natural resource agencies wanting to improve Latinx outdoor recreation experiences should have bilingual front-line staff and provide communicative media, such as website information or on-site signage, in Spanish. Our findings also underscore the importance of Latinx-focused social media groups as useful tools for disseminating information.

A Mixed Methods Study on Character Traits of Nursing Students and Faculty Influencing a 100% Passing Rate in the Nursing Licensure Exam in the Philippines.

This study explores the character traits contributing to the 100% passing rate of nursing graduates in the Nursing Licensure Examination (NLE) in the Philippines over the past decade. Understanding these traits provides insights into the factors driving academic and professional success in nursing. Employing a convergent parallel mixed methods design, this study combined quantitative and qualitative approaches. Data were collected through electronic surveys from 222 nursing alumni and 39 faculty members, focusing on character traits and behaviors linked to NLE success. The quantitative data were analyzed using Statistical Product and Service Solutions (SPSS, version 29; IBM SPSS Statistics for Windows, Armonk, NY) for descriptive statistics and factor analysis. Additionally, in-depth interviews with 21 alumni and 15 faculty members provided qualitative insights. Data saturation was reached with 11 faculty and 13 alumni, ensuring comprehensive coverage of the participants' experiences. Quantitative results from factor analysis showed that spirituality, love of learning, honesty, and kindness are among the qualities that are necessary for success in NLE. These character traits have a significant impact on both career readiness and academic performance. Qualitative results revealed the importance of resilience, faculty support, and peer relationships in fostering these attributes. It became evident that building a healthy learning environment required the support of peers and professors and that resilience was necessary to manage the stress of tests. Both datasets emphasized the need for a strong character and academic achievement in conjunction with long-term success. The study highlights that obtaining a high NLE passing rate is mostly dependent on academic knowledge in addition to character attributes. Character education techniques such as role-playing, reflective writing, and service-learning can be incorporated into nursing curricula to improve attributes such as empathy and resilience. Continuous faculty development and structured mentorship are also crucial. Character development must be incorporated into academic learning in nursing education. Focusing on qualities such as empathy, resilience, and ethical judgment, along with implementing character education tactics such as service-learning and reflective writing, are crucial to prepare graduates to succeed in professional practice and board exams. A comprehensive approach that blends character development with academic achievement produces skilled and compassionate healthcare professionals.

Perceived structural empowerment, resilience, and intent to stay among midwives and registered nurses in Saudi Arabia: a convergent parallel mixed methods study

BackgroundRetaining midwives and registered nurses in the Obstetrics and Gynecology department/unit (OB/GYN) is not just a matter of organizational effectiveness and financial wellness. It’s a crucial aspect of ensuring quality healthcare delivery. This study aimed to discuss the degree to which midwives and nurses in OB/GYN departments are structurally empowered, resilient, and committed to remaining at the organizations and to examine whether nurses’ and midwives’sense of structural empowerment and resilience is a good predictor of their decision to stay with the organization.MethodsThis study employed a unique convergent parallel mixed methods approach. The research was conducted in two distinct phases. The first phase involved a cross-sectional quantitative survey with a convenience sample of 200 midwives and nurses in OB/GYN departments. The second phase was a qualitative study utilizing semi-structured, open-ended interviews. Eighteen nurses and midwives, specifically chosen as the target population, were invited to participate in individual interviews. The data collection took place at three major hospitals in Saudi Arabia, starting in January 2023 and concluding in February 2023.ResultsThe study results revealed that structural empowerment and resilience were statistically significant predictors of the intent to stay in the organization (F = 35.216, p < 0.001), with 26.3% variation, the structural empowerment is higher predictor (β = 0.486, p < 0.000) to intent to stay if compared to resilience (β = 0.215, p < 0.008). Five major themes emerged from the narratives of the nurses and midwives: the nurturing of the physical and physiological, the development of the psychological, the managing finances, the restructuring of the organization, and the enrichment of the professional and occupational.ConclusionThe study’s findings have significant implications for healthcare organizations. They highlight the importance of cultivating a culture of empowerment and resilience, which can serve as a powerful tool to encourage registered nurses and midwives to remain in their organizations. This insight empowers healthcare administrators, human resource managers, and obstetrics and gynecology professionals to take proactive steps toward improving retention rates.

Tumor classification algorithm via parallel collaborative optimization of single- and multi-objective consistency on PET/CT

Malignant tumors still have a high incidence and mortality rate worldwide. Pathological examination remains the clinical gold standard for tumor diagnosis. However, some patients cannot undergo pathological examination due to advanced age and special lesion location. Therefore, making full use of PET/CT to assist doctors in tumor classification has important clinical significance. Since category labels are calibrated according to pathological images, it is difficult to obtain effective pathological category features directly using PET-CT image modeling. In response to this problem, this paper proposes a novel tumor classification algorithm. This method fully utilizes multi-gray-level 3D gray-level co-occurrence matrix and the proposed rough and fine constraint network under the constraint loss of rough and fine labels. Based on single- and multi-objective consistency, a parallel collaborative optimization method is proposed, including category consistency loss and feature specificity loss. To reduce the interference of redundant features, an improved Boruta feature selection method using multiple classifiers and multiple steps is proposed. The final result is obtained through a conditional weighted voting function. The proposed method shows excellent performance in both the submodels and the fusion model. We validated the proposed tumor classification method on three datasets and achieved good performance with the accuracy of 0.80–0.85 and F1-score of 0.78–0.88. The results indicate that the proposed method has good performance and generalization ability.

Patient acceptance of care of a novel care pathway for those at risk of poor outcomes from musculoskeletal pain: A mixed methods study

ObjectiveInvestigate people's acceptance of specialist musculoskeletal care within a new care pathway for common musculoskeletal conditions (low back pain, neck pain/whiplash, knee osteoarthritis). DesignConvergent parallel mixed methods design referencing the Theoretical Framework of Acceptability. The study included a subset of participants (n = 29) at-risk of poor outcomes from the intervention arm of the PAthway of CarE for common musculoskeletal conditions (PACE-MSK) trial. In the PACE-MSK arm, participants received specialist physiotherapist care as an adjunct to the care provided by their primary healthcare professional(s). One-to-one semi-structured interviews were conducted around 3-months after commencing in the trial. Quantitative data were collected at baseline and 3-month follow-up (health-related quality of life, pain self-efficacy, global perceived change, satisfaction). ResultsFive themes were identified (Expectations and beliefs shaped patient experience; Clinical expertise and competence influence acceptance; Person-centred care; Mechanisms facilitating beneficial responses to care; Gaps in care pathway implementation). There were positive individual changes in physical quality of life for 17/29 (59%) participants, mental health quality of life for 12/29 (41%), pain self-efficacy for 8/29 (28%) and global perceived change for 19/29 (66%). Management met expectations with the majority reporting high levels of satisfaction. Integrating the qualitative and quantitative data with the Theoretical Framework of Acceptability, there were complementary meta-inferences in the constructs of ‘ethicality’, ‘intervention coherence’, ‘self-efficacy’ and ‘affective attitude’. Divergence was identified in ‘perceived effectiveness’. DiscussionIn general, there was positive acceptance of the care pathway by participants. Specialist physiotherapists’ care was perceived as a positive addition to usual care.

POSE: POSition Encoding for accelerated quantitative MRI

Quantitative MRI utilizes multiple acquisitions with varying sequence parameters to sufficiently characterize a biophysical model of interest, resulting in undesirable scan times. Here we propose, validate and demonstrate a new general strategy for accelerating MRI using subvoxel shifting as a source of encoding called POSition Encoding (POSE). The POSE framework applies unique subvoxel shifts along the acquisition parameter dimension, thereby creating an extra source of encoding. Combining with a biophysical signal model of interest, accelerated and enhanced resolution maps of biophysical parameters are obtained. This has been validated and demonstrated through numerical Bloch equation simulations, phantom experiments and in vivo experiments using the variable flip angle signal model in 3D acquisitions as an application example. Monte Carlo simulations were performed using in vivo data to investigate our method's noise performance. POSE quantification results from numerical Bloch equation simulations of both a numerical phantom and realistic digital brain phantom concur well with the reference method, validating our method both theoretically and for realistic situations. NIST phantom experiment results show excellent overall agreement with the reference method, confirming our method's applicability for a wide range of T1 values. In vivo results not only exhibit good agreement with the reference method, but also show g-factors that significantly outperforms conventional parallel imaging methods with identical acceleration. Furthermore, our results show that POSE can be combined with parallel imaging to further accelerate while maintaining superior noise performance over parallel imaging that uses lower acceleration factors.

The role of liquefaction in the evolution of shallow submarine canyon heads from a geotechnical perspective: A case study of the Garrucha Canyon (SE Mediterranean)

This work aims to establish the role of liquefaction in a shallow submarine environment defined by a canyon head reaching the coast. The study area is the Garrucha submarine canyon head, which is located in the western Mediterranean Sea.The potential of liquefaction is approached empirically by two methods in parallel, undrained cyclic direct simple shear (UCDSS) test and piezocone penetration test (CPTu) analyses. For both approaches, considering the regional earthquake records, a cyclic load linked to Mw ≤ 6.5 earthquake events or a maximum ground surface acceleration amax of 0.25 g is considered.The sediment samples analysed are nonplastic sands with low silt/clay contents and can be defined as liquefiable. Geotechnical analysis reveals a high probability of triggering liquefaction in this kind of sediment at depths greater than 3 m below the seafloor. CPTu records are used to assess and improve the liquefaction model for the study area by defining 3 different stratigraphic configurations or liquefiable conditions: uniformly liquefiable, interbedded liquifiable and nonliquefiable.This work highlights the importance of liquefaction—a process normally underestimated in submarine environments—in the downslope transport of sediment from the upper part of a canyon and, more generally, in canyon head evolution with different potential morphosedimentary consequences.

Random distribution of asphalt and cement mortar in semi-flexible pavement: Implication for cracking resistance

The distribution characteristics of asphalt and cement mortar play a crucial role in determining the cracking resistance of semi-flexible pavements (SFP). In this study, digital image processing technology was utilized to quantify the thickness distribution of asphalt and cement mortar within SFP, and a parallel line segmentation method was employed to characterize the random distribution of mortar thickness (RDMT) of asphalt and cement mortar. Variance, coefficient of variation (COV), and interquartile range were proposed to characterize RDMT, examining the effects of air voids (AV) content, nominal maximum aggregate size (NMAS), and compaction method on RDMT, and its variation along the specimen height. Semi-circular bending test was conducted to evaluated the cracking resistance of SFP, exploring the relationship between RDMT and cracking resistance. Results indicate that parallel line segmentation method with 36 parts and 25 parts is recommended to characterize the RDMT of asphalt and cement mortar, respectively. An increase in AV content led to a higher RDMT for asphalt mortar but a lower RDMT for cement mortar. Conversely, as NMAS increased, the average thickness of asphalt and cement mortar increased, while the RDMT of asphalt mortar decreased and that of cement mortar increased. RDMT of asphalt and cement mortar is higher under Superpave gyration compaction method compared to the Marshall compaction method. Additionally, RDMT increased from the top to the bottom of the specimen height. Based on the RDMT, a random distribution index (RDI) was proposed, which exhibited a strong linear relationship with the cracking resistance of SFP. When the RDI decreased by 44.4 %, the corresponding cracking resistance of SFP increased by 84.0 %. Improving the distribution of asphalt and cement mortar could enhance the cracking resistance of SFP.

Assessing speaking proficiency of English teachers through self-assessment test: East Wollega zone in focus

This study addresses the significant role of English speaking proficiency in the teaching-learning process, particularly considering the questionable speaking abilities of English teachers. The research aims to assess the speaking proficiency of English teachers in the East Wollega Zone. Employing a convergent parallel mixed design, blending quantitative and qualitative data methods, self-assessment tests, and classroom observations were utilized for data collection, and 101 participants for self-assessment and 15 respondents for classroom observations were selected using simple random sampling method. Findings indicate a prevalent trend of low speaking proficiency among English teachers, supported by both self-assessment data (mean= 2.3, standard deviation= 0.62) and classroom observation records. While gender did not significantly influence self-assessment scores, significant differences were noted among education qualification levels and teaching experience groups. Multiple regression analysis revealed a moderate association (R2= 44.1%) between independent and dependent variables. The study concludes with implications underscoring the urgent need to enhance English teachers’ speaking competency, particularly in first-cycle primary schools in the East Wollega Zone, emphasizing the potential to elevate the quality of the teaching-learning process and improve students' language acquisition and overall educational outcomes.

HEAD TEACHERS' CANDIDATE PREPARATION STRATEGIES AND STUDENTS’ PERFORMANCE IN THE PRIMARY CERTIFICATE OF EDUCATION IN CHIMOIO DISTRICT, MOZAMBIQUE

The purpose of this study was to investigate the influence of head teachers' candidate preparation strategies on students’ performance in the Primary Certificate of Education in Chimoio District, Mozambique. The objectives of this study were: to examine the influence of examination anxiety management on students’ academic performance and to evaluate the influence of motivation strategy on students’ academic performance in the Primary Certificate of Education in Chimoio District, Mozambique. A convergent parallel mixed method design was used. The study adopted a cross-sectional survey research design for quantitative data and a phenomenological design for qualitative data. The focus was on public primary schools, head teachers, teachers and Mozambique’s Ministry of Education officer. Simple random sampling was used to select 18 out of 23 primary schools and 125 out of 312 teachers; criterion purposive sampling was used to select 18 head teachers and 1 Ministry of Education officer. Proportionate sampling, simple random sampling, was used to select 316 out of 1500 students. Questionnaires were used to collect data from students and teachers. An interview guide was used to collect data from head teachers and the Ministry of Education officer. Instrument reliability was tested using the test-retest technique, where a score of 0.82 was realized. Quantitative data was analyzed using SPSS version 25, and findings were reported in percentages, frequency tables, and graphs. The qualitative data were analyzed into themes according to the research questions and reported in narratives and direct quotations. The study revealed that head teachers’ candidate preparation strategies, including, exam anxiety management and student motivation, have an influence on students’ academic performance in the Primary Certificate of Education in Chimoio District, Mozambique. The study recommended that in preparing candidates for examinations, head teachers should prioritize and promote intrinsic motivation strategies. These include fostering a supportive learning environment, encouraging student autonomy, and emphasizing the value of learning itself. Such strategies are expected to have a more sustainable and positive impact on student engagement and academic performance.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0615/a.php" alt="Hit counter" /&gt;&lt;/p&gt;