Time Allocation Research Articles

From unobserved to observed preference heterogeneity: a revealed preference methodology

AbstractWe present an easy‐to‐apply non‐parametric revealed preference method to identify observed preference heterogeneity from cross‐sectional data. Building on the partitioning approach that was developed by Crawford and Pendakur (Economic Journal, 2013, 123(567), 77–95) and Cosaert (Computational Economics, 2019, 53(2), 533–54), it quantifies the contribution of observable consumer characteristics to describing the identified preference heterogeneity. We demonstrate the practical usefulness of our method through an application to newly gathered experimental data on consumer choice behaviour in two types of decision situations: the allocation of money (choosing between two products) and the allocation of time (choosing between leisure and work). We investigate whether the same consumer characteristics drive the observed variation in choice behaviour in these two settings.

Sex differences in foraging ecology of a zooplanktivorous little auk Alle alle during the pre-laying period: insights from remote sensing and animal-tracking

BackgroundEnergy and time allocation in seabirds differ between consecutive stages of breeding given various requirements of particular phases of the reproductive period. Theses allocations may also be sex-specific considering differential energetic or nutritional requirements of males and females and/or sexual segregation in foraging niches and/or areas. In this study we investigated the foraging ecology of an Arctic, zooplanktivorous seabird, the little auk Alle alle during the pre-laying period using remote sensing of the environment and GPS-TDR loggers deployed on birds. We compared foraging trips range and habitats of birds with other stages of the breeding period and between sexes.ResultsWe found that little auks during the pre-laying period foraged exclusively in cold sea surface temperature zones (with temperatures < 5 ºC) but in various sea depth zones. They dived to similar depths ranging from -4.0 to -10.9 m, exploring various thermal microhabitats (with mean temperatures values ranging from 2.2 °C in Shelf sea depth zone to 5.9 °C in Deep sea depth zone). The majority of foraging trips and dives characteristics were similar to subsequent phases of breeding. However, home ranges during the pre-laying trips were wider compared to the incubation period. As expected, females exhibited wider foraging niches compared to males (wider range of sea surface temperature and sea depth in foraging locations), which could be explained by sex specific energetic and/or nutritional requirements (females producing an egg). We also delineated local foraging areas important for little auks during their whole breeding season. Protection of these areas is crucial for sustaining the local marine biodiversity.ConclusionsWe found that little auks females during the pre-laying period explored wider foraging niches compared to males. These differences may be attributed to sex-specific nutritional or/and energetical constraints at this stage of breeding. The results of this study also emphasize the importance of shelf Arctic-type water masses as the foraging areas for little auks during successive stages of breeding.

Time-triggered scheduling of mixed-critical flows at end-system in asynchronous AFDX avionic network

Avionics Full-DupleX (AFDX) is a switched Ethernet-based network used in modern commercial airplanes for the transmission of command and control avionics flows. These critical flows require deterministic guarantees leading to a lightly loaded network. Aircraft manufacturers envision to carry additional non avionics flows (i.e. video, audio, service) to take advantage of the spare bandwidth. However, it is then compulsory to preserve the real-time guarantees of avionics flows in terms of bounded jitter at the transmitter output and of bounded end-to-end latency. Depending on the type of additional traffic, Quality of Service (QoS) end-to-end guarantees may be offered to the additional flows of lower criticality in terms of reduced delay or bounded jitter for instance. These guarantees can be ensured by scheduling policies at transmitter and switch level. However, an important safety-related constraint is the asynchronous design of avionics distributed systems that prohibits the use of a network-wide synchronization of end systems and switches. Thus, time-triggered networking such as emerging Time-Triggered Ethernet (TTEthernet) or Time-Sensitive Networking (TSN) cannot be leveraged. This paper underlines the benefits of only scheduling flows at the transmitter, which is compatible with the asynchronous safety constraint of avionics systems. We show that it is possible to build a table schedule that carries both critical avionics flows and additional video flows that meet their timing and bandwidth allocation constraints. Therefore, we design scheduling strategies for efficient distribution of flows in the table scheduling whose performance is compared to the optimal schedule minimizing the emission lag of additional flows. Proposed heuristics are constructed such as to favor the network responsiveness for avionics flows thanks to slot over-provisioning. Extensive results on an A350 AFDX industrial configuration show that for a transmitter load of up to 70% of the available bandwidth, the uniform allocation heuristic provides a performance close to optimal in terms of minimum emission lag for additional flows, so offering a practical configuration heuristic to industry.

Measuring Panic as a Facet of Anxiety on Students’ Oral and Written Assessment in The University of Bamenda, Cameroon

Aim: The growing concern about the declining academic performance of students in Cameroon schools and colleges provokes varied reflections on the possible factors. One, but less obvious issue is anxiety, manifested in forms like agitation, excessive worrying, restlessness, and panic. While these variants are all critical in appreciating the connections with classroom assessment, this paper primarily isolates and focuses on panic, given its common visible expression among students. Specifically, the paper centers on how panic affects the performance of students in oral and written classroom assessments at the University of Bamenda.&#x0D; Methods: Systematic random and purposive sampling techniques were used to select 327 second-year students from the Faculty of Arts, Higher Teacher Training College, and the Faculty of Science to participate in the study. A sequential explanatory research design aided by a structured questionnaire, interview, and observation was used to collect quantitative and qualitative data. The qualitative data were analyzed using descriptive statistics, while the likelihood ratio test was used to test the hypothesis. &#x0D; Results: The findings showed that panic has a high significant effect on students’ performance in assessment (Chi-square = 232.054, df = 60, P = 0.000, far &lt;0.05).&#x0D; Conclusion: The findings indicated, among others, that when students exhibit panic during assessments, they lose concentration, forget what they studied, easily make errors, and experience disorganized speech, especially during oral assessments.&#x0D; Recommendation: To reduce this type of anxiety during assessment, there is a need for intensive rehearsals before assessment, the avoidance of panic triggers, especially from invigilators, and fairness in time allocation for both oral and written assessments.

Expert teleconsultation involving patients and their primary neurologists for the management of multiple sclerosis in regions without specialists

AbstractObjectiveThis study aimed to describe the usefulness of our teleconsultation system for managing multiple sclerosis (MS) in regions without specialists.MethodsA cross‐sectional questionnaire survey involving 11 MS patients and their primary neurologists was carried out between May and December 2023. Real‐time video conferences were conducted between an MS specialist at a hub hospital and patients with their primary neurologists at one of the four regional core hospitals in Hokkaido, Japan. Patients and their primary neurologists completed questionnaires to evaluate the usefulness of the teleconsultation system.ResultsThe patients and their primary neurologists were generally satisfied with the teleconsultations and expressed willingness to continue using the system. In particular, alleviating the burden of visiting distant MS‐specialized clinics was highly appreciated by patients. In addition, patients gave high scores for questions regarding increased satisfaction with the primary neurologists' care and the treatments they offered. The primary neurologists thought the system enhanced their knowledge of MS management. However, they did not think that the system could ease their burden for managing MS patients because of challenges in time allocation and scheduling for teleconsultation sessions.ConclusionsThe present study suggested that our expert teleconsultation system for MS reduces the burden on patients of visiting distant MS‐specialized clinics, and enhances knowledge of MS management for the primary neurologists. It also promotes trust between patients and their primary neurologists, and taken together, these aspects could collectively lead to independent and sustainable MS management in regions without MS specialists.

Business scholars’ time allocation under the lens of the self-managed approach of academic’s role and the outcome-focused perspective of university’s strategic management

PurposeThis article explores whether six broad categories of activities undertaken by Canadian business scholars’ academics: publications record, citations record, teaching load, administrative load, consulting activities, and knowledge spillovers transfer, are complementary, substitute, or independent, as well as the conditions under which complementarities, substitution and independence among these activities are likely to occur.Design/methodology/approachA multivariate probit model is estimated to take into account that business scholars have to consider simultaneously whether or not to undertake many different academic activities. Metrics from Google Scholar of scholars from 35 Canadian business schools, augmented by a survey data on factors explaining the productivity and impact performances of these faculty members, are used to explain the heterogeneities between the determinants of these activities.FindingsOverall, the results reveal that there are complementarities between publications and citations, publications and knowledge spillovers transfer, citations and consulting, and between consulting and knowledge spillovers transfer. The results also suggest that there are substitution effects between publications and teaching, publications and administrative load, citations and teaching load, and teaching load and administrative load. Moreover, results show that public and private funding, business schools’ reputation, scholar’s relational resources, and business school size are among the most influential variables on the scholar’s portfolio of activities.Originality/valueThis study considers simultaneously the scholar’s whole portfolio of activities. Moreover, the determinants considered in this study to explain scholars’ engagement in different activities reconcile two conflicting perspectives: (1) the traditional self-managed approach of academics, and (2) the outcomes-focused approach of university management.

Nurses’ perspectives on professional self-concept and its influencing factors: A qualitative study

BackgroundNurses with a strong professional self-concept tend to exhibit a positive mindset and strong work engagement, delivering high-quality patient care. Although numerous quantitative studies have examined the factors impacting professional self-concept, there remains a limited exploration of these factors from the perspective of nurses themselves.MethodsThis qualitative descriptive study uses the PERMA theory and Social Cognitive Theory as the theoretical framework. Semi-structured interviews were conducted with 15 nurses from six public hospitals in China. The data were analyzed thematically using a combination of inductive and deductive approaches.ResultsNurses’ understanding of professional self-concept could be divided into four categories: professional identity, competence, care, and knowledge. Factors influencing nurses’ professional self-concept were categorized into eight subthemes in three domains: (1) personal factors, including psychological qualities and attitude towards the nursing profession; (2) occupational-related behavioral factors, including role-oriented behavior and knowledge-oriented behavior; and (3) work environment and external factors, including external evaluation and perceptions of nurses, time allocation, nursing work tasks, work atmosphere, school education, and perceived supports.ConclusionsThis study found that, although nurses had different personal experiences, their perceptions of professional self-concept were similar. Nurses’ professional self-concept is a multidimensional concept and involves various factors, such as personality, work-related characteristics, environment, and family. To thrive in a nursing career, nurses must discern the factors that can enhance or hinder their professional self-concept. By identifying and adjusting these factors, personalized support and positive interventions can be tailored to meet nurses’ specific needs, which ultimately nurtures their professional development.Trial registrationThis study was registered on December 14, 2022, in the Chinese Clinical Trial Registry (ChiCTR2200066699) as part of our ongoing study.

Leveraging AI for Enhanced Quality Assurance in Medical Device Manufacturing

The medical device sector adheres to strict regulatory frameworks, requiring precise adherence to quality assurance (QA) processes during the production process. Conventional quality assurance (QA) approaches, although successful, sometimes require substantial time and resource allocations, resulting in possible obstacles and higher expenses. The emergence of Artificial Intelligence (AI) in recent years has completely transformed quality assurance (QA) methods in different sectors, providing unparalleled prospects for improved productivity, precision, and scalability. This research examines the possibility of using AI technologies to enhance quality assurance processes in the manufacturing of medical devices. Manufacturers may improve product quality and streamline production workflows by utilising AI techniques like machine learning, computer vision, and natural language processing to automate and optimize important QA procedures. Artificial intelligence systems can analyse large amounts of data to find abnormalities, uncover flaws, and anticipate any problems in real-time. This allows for proactive intervention and reduces the chances of non-compliance hazards. In addition, AI-powered QA systems provide adaptive learning capabilities, constantly enhancing performance through feedback and adapting to changing regulatory needs. The incorporation of artificial intelligence (AI) into current quality management systems enables smooth and efficient sharing of data and compatibility, promoting a comprehensive approach to quality control throughout the whole production process.

Enhancing Throughput in IoT Networks: The Impact of Active RIS on Wireless Powered Communication Systems

This paper investigates the potential of active reconfigurable intelligent surfaces (RIS) to enhance wireless-powered communication networks (WPCNs), addressing the evolving connectivity needs of the internet of things (IoT). Active RIS, capable of amplifying and reflecting signals, offers a solution to surpass the limitations of passive RIS, such as double-fading attenuation, aiming to significantly improve network throughput and coverage. Our research focuses on exploiting the amplification capabilities of active RIS to boost the overall network sum throughput, engaging in a comprehensive optimization of critical network parameters, including time allocation, reflection coefficients, and phase shift matrices specific to active RIS. The formulated problem is non-convex and highly complex due to the coupling of optimization variables. We employed a successive convex approximation algorithm to solve the throughput maximization problem by converting the non-convex constraints into approximated convex constraints and solving them iteratively. Through extensive simulations, we demonstrate that our active RIS-assisted network substantially outperforms networks facilitated by passive RIS, marking a significant advancement in WPCN performance. These findings underscore the potential of active RIS technology in realizing the full capabilities of IoT connectivity.

Evaluation of time allocated for bid preparation in national competitive bidding in the Sri Lankan construction industry

PurposeInsufficient time allocation for the bidding period occurs, causing drawbacks to both parties, the client and the bidder. Hence, this study aims to evaluate the time allocated for preparing a bid proposal as per the National Competitive Bidding (NCB) in the Sri Lankan context.Design/methodology/approachThe study has adopted a mixed method approach and expert interviews and document review to detect, analyse and validate the issues, and solutions based on NCB along with the adequacy of the allocated bidding period used as main data collection tools. Both qualitative and quantitative data were analysed through manual content analysis and inferential analysis respectively.FindingsOverall, 24 local issues with the existing competitive bidding process and solutions for each were identified. Among the 24 local issues, it was unanimously agreed by all interviewees that three specific issues require attention and improvement. These issues are related to the standard and incompleteness of bidding documents, inaccurate BOQ quantities measured by the consultant or the main contractor, and the excessive number of bidding document amendments by the consultant. It was revealed that a maximum of 42 calendar days (6 weeks) is sufficient for the bidding process while a minimum of 21 calendar days (3 weeks) is insufficient.Originality/valueThe findings of this study would be recommended that Information and Communication Technology Agency (ICTA) understand the necessity of revising the NCB reference to the time allocated for the preparation of bids. By recognising the importance of sufficient time allocation for bid preparation, this research serves as a practical guide for authorities involved in policy formulation, aiding them in implementing revisions that align with the dynamic requirements of bidding procedures.

HumanLight: Incentivizing ridesharing via human-centric deep reinforcement learning in traffic signal control

Single occupancy vehicles are the most attractive transportation alternative for many commuters, leading to increased traffic congestion and air pollution. Advancements in information technologies create opportunities for smart solutions that incentivize ridesharing and mode shift to higher occupancy vehicles (HOVs) to achieve the car lighter vision of cities. In this study, we present HumanLight, a novel decentralized adaptive traffic signal control algorithm designed to optimize people throughput at intersections. Our proposed controller is founded on reinforcement learning with the reward function embedding the transportation-inspired concept of pressure at the person-level. By rewarding HOV commuters with travel time savings for their efforts to merge into a single ride, HumanLight achieves equitable allocation of green times. Apart from adopting FRAP, a state-of-the-art (SOTA) base model, HumanLight introduces the concept of active vehicles, loosely defined as vehicles in proximity to the intersection within the action interval window. The proposed algorithm showcases significant headroom and scalability in different network configurations considering multimodal vehicle splits at various scenarios of HOV adoption. Improvements in person delays and queues range from 15% to over 55% compared to vehicle-level SOTA controllers. We quantify the impact of incorporating active vehicles in the formulation of our RL model for different network structures. HumanLight also enables regulation of the aggressiveness of the HOV prioritization. The impact of parameter setting on the generated phase profile is investigated as a key component of acyclic signal controllers affecting pedestrian waiting times. HumanLight’s scalable, decentralized design can reshape the resolution of traffic management to be more human-centric and empower policies that incentivize ridesharing and public transit systems.

The equation for medical multiple-choice question testing time estimation.

Multiple-choice questions (MCQs) offer a suitable means to assess the cognitive domain of learners with a high degree of objectivity. The study's objective is to formulate an equation for determining the ideal timing for MCQ examinations, thereby inspiring the development of a model to estimate the duration of these examinations. The authors generated a specific computer program that integrated with the operating system of the examination. Technical-specific features included the ability to calculate the speed of students taking examinations with images or videos in the questions or options. This bespoke computer program was designed specifically for assessing individual students' MCQ test-taking pace and generating a proctor report in a computer-readable format. Subsequently, data derived from this program underwent regression analysis to determine the speed at which students completed MCQ examinations. The data were collected from a total of 1035 examinees, all of whom were non-native English speakers. The average reading rate was 62.38±20.4 words/min. It was found that the rate decreased significantly in difficult (50.65±6.9 words/min) items compared to easy (82.29±21.3 words/min) and intermediate (60.56±19.1 words/min) items (p<0.001), respectively. The linear regression analysis predicted option selection (words/min) as; 33.92+1.93(%tables/figures)+0.14(%recall)-0.37(%application), r2=0.45, p<0.001. It is not advisable to base the decision solely on reading time or time allocation. Examination administrators are advised to proactively plan ahead, with particular emphasis on establishing a well-defined taxonomy, as it constitutes a fundamental cornerstone in the utilization of the estimation equation.

Enhancement of Cryptocurrency Mining through Artificial Intelligence for Workstation Systems

For workstation computers, it is highly recommended to use AI-powered bitcoin mining to maximise processing time and resource allocation. Conventional PC mining systems have a number of difficulties, such overheating, system availability algorithms, and controlling power consumption in relation to bitcoin production. The study has introduced an AI board called LSAI48266x in order to encounter the traditional PC mining systems. It uses intelligent algorithms to solve the problems existence with traditional PC based crypto mining. Even in the absence of human workers at the workstation PCs, LSAI48266x detects the best times to mine cryptocurrency by incorporating a variety of variables. The goal of the suggested solution is to minimise total electricity use while optimising CPU power utilisation. Using AI to increase computer resource efficiency during idle times is the major goal of the idea, which also aims to reduce excessive power consumption, preserve system dependability, and increase income.

Visitors' consistent stay behavior patterns within free-roaming scenic architectural complexes: Considering impacts of temporal, spatial, and environmental factors

GPS positioning data are increasingly utilized in environmental behavior studies to explore the spatial-temporal behavioral patterns of individuals. However, individuals' stay behavioral pattern and its influencing factors, which are particularly significant for the design and management of scenic architectural complexes, have not been thoroughly examined. Using GPS trajectory data collected from the Palace Museum in Beijing (China), this paper investigated the visitors' stay behavior patterns associated with temporal, spatial, and environmental influencing factors. Types of stay behavior and characteristics of stay in main stay areas were automatically recognized using Python algorithms for further and quantitative analysis. Results showed that visitors' stay time exhibited a consistent pattern regarding psychological time allocation, a relatively unsignificant pattern regarding lunch hour, and no clear pattern regarding fatigue feature. Grouped regression analysis showed positive linear relationships with similar slopes between the average stay length and the number of stay occurrences in each type of stay area. Partial correlation analysis revealed the underlying connection between the impact of seats and greenery on stay behavior. Individually, each of the two environmental elements showed limited effect on stay frequency and stay length, while incorporating greenery into seating areas would notably increase both stay frequency and stay length.

Trajectory optimization of unmanned surface vehicle based on improved minimum snap

To solve the problem of path discontinuity and tracking difficulty in unmanned surface vehicle path planning, this paper introduces the Minimum Snap algorithm to optimize the trajectory, and makes some improvements to the Minimum Snap algorithm to address the problem of imperfect paths caused by uneven time allocation. The concept of a safe corridor is introduced to optimize the Minimum Snap algorithm. In response to the problem of excessive deviation from the reference value in some areas of the optimized path, a guidance function is added to make the path closer to the original trajectory. In the simulation, the proposed improved Minimum Snap is compared with Bezier curve and B-spline curve, the results show that the improved Minimum Snap can enable unmanned surface vehicle to complete turns and other actions with minimal energy consumption while driving safely, without experiencing severe acceleration and Jerk, laying the foundation for subsequent path tracking control.

The impact of machine translation on the development of info-mining and thematic competences in legal translation trainees: a focus on time and external resources

ABSTRACT This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator’s research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic competences in legal translation. Data were elicited through a translation task completed by a cohort of 110 final-year MA trainees with training in legal translation and basic MT literacy, and a cohort of 54 first-year MA trainees with no to very limited experience in specialised translation and post-editing. This paper provides a first analysis of selected process-related data concerning the allocation of time and the use of external resources throughout the translation or post-editing processes of 40 participants, 20 from each cohort. Preliminary results highlight some correlations between the use of time and external resources and both (a) the development of thematic and info-mining competences and (b) the specific type of task, i.e. whether from-scratch translation or post-editing.

An AI-based multiphase framework for improving the mechanical ventilation availability in emergency departments during respiratory disease seasons: a case study

BackgroundShortages of mechanical ventilation have become a constant problem in Emergency Departments (EDs), thereby affecting the timely deployment of medical interventions that counteract the severe health complications experienced during respiratory disease seasons. It is then necessary to count on agile and robust methodological approaches predicting the expected demand loads to EDs while supporting the timely allocation of ventilators. In this paper, we propose an integration of Artificial Intelligence (AI) and Discrete-event Simulation (DES) to design effective interventions ensuring the high availability of ventilators for patients needing these devices.MethodsFirst, we applied Random Forest (RF) to estimate the mechanical ventilation probability of respiratory-affected patients entering the emergency wards. Second, we introduced the RF predictions into a DES model to diagnose the response of EDs in terms of mechanical ventilator availability. Lately, we pretested two different interventions suggested by decision-makers to address the scarcity of this resource. A case study in a European hospital group was used to validate the proposed methodology.ResultsThe number of patients in the training cohort was 734, while the test group comprised 315. The sensitivity of the AI model was 93.08% (95% confidence interval, [88.46 − 96.26%]), whilst the specificity was 85.45% [77.45 − 91.45%]. On the other hand, the positive and negative predictive values were 91.62% (86.75 − 95.13%) and 87.85% (80.12 − 93.36%). Also, the Receiver Operator Characteristic (ROC) curve plot was 95.00% (89.25 − 100%). Finally, the median waiting time for mechanical ventilation was decreased by 17.48% after implementing a new resource capacity strategy.ConclusionsCombining AI and DES helps healthcare decision-makers to elucidate interventions shortening the waiting times for mechanical ventilators in EDs during respiratory disease epidemics and pandemics.

IMPLENTASI PEMBELAJARAN AQIDAH AKHLAQ DALAM PEMBENTUKAN KARAKTER RELIGIUS SISWA DI MTS MIFDA PRIMA KABUPATEN PROBOLINGGO

This study aims to explore the implementation of Islamic Moral Education in shaping religious character among students at MTS Mifda Prima Probolinggo, as well as to identify the supporting and hindering factors, along with the outcomes of applying this educational approach at MTS Mifda Prima Probolinggo. The research was conducted at MTS Mifda Prima Probolinggo, involving both the Islamic moral education teachers and the students as research subjects and informants. The applied method in this research is qualitative descriptive, where data, both written and oral, regarding the research subjects, are detailed. Data collection is carried out through observation, interviews, and documentation. Data analysis is performed using the Miles and Huberman approach, involving data reduction, data display, and drawing conclusions. The research findings indicate that the implementation of Islamic Moral Education in shaping religious character among students at MTS Mifda Prima Probolinggo is carried out through exemplary and habituation methods. This includes incorporating pre-lesson prayers, communal prayers, participating in the Tahsinul Qur'an program, fostering commendable behavior, and showing respect to teachers and peers. The goal is to support the formation of religious values that can be applied in daily life and provide positive examples. Identified hindering factors involve inadequate time allocation and the behavior of students.

Differential Impact of Sharecropping on Time Allocation and Risk Transfer in Farming: An Islamic Economic Perspective

This study presents a quantitative exploration of the influence of sharecropping on the allocation of time and risk transfer in farming practices. Through a causal associative research design, the study identifies various factors of influence on the dependent variable, applying an Ordinary Least Squares (OLS) regression analysis on survey data. The results provide intriguing insights into farmers' decision-making and preferences concerning cooperation models based on land ownership status. Our findings reveal that shareholder farmers, who farm lands belonging to others, exhibit preferences distinct from owner-farmers for cooperative models. Similarly, those cultivating both others' and their own lands demonstrate unique inclinations towards different cooperative models compared to owner-farmers. The results also emphasize the significance of risk perceptions in these preferences. A significant tendency was observed among farmers to allocate more time to farming when they are relieved of risk entirely in an agricultural management scenario, particularly in long-duration collaborations. In contrast, owner-farmers and those cultivating both their own and others' land exhibited a more cautious approach, agreeing to share risks but within limited periods of cooperation. These findings contribute to a nuanced understanding of the effects of sharecropping on farmers' time management and risk-allocation decisions, providing significant implications for agricultural policy and practices. Further research should delve into the psychosocial factors that influence these preferences to enable the creation of more equitable and efficient farming systems.

Strategi Pemecahan Masalah Pendidikan Agama Islam di Kampus Akademi Farmasi Dwi Farma Bukittinggi

This study examines problem-solving strategies for Islamic religious education in pharmacy campus environments, motivated by the importance of Islamic education in shaping students' character, ethics, and morals, as well as the unique challenges of integrating Islamic values with modern pharmaceutical science. The main issues identified include lack of student interest and motivation, difficulties in integrating religious values with pharmacy materials, limited time and lesson allocations, and insufficient facilities supporting religious activities. The research aims to discover appropriate strategies to address these issues and enhance the effectiveness of Islamic education in pharmacy campuses. The findings reveal several key strategies that can be implemented, including: establishing binding regulations, organizing meetings with off-campus religious lecturers, coordinating with student affairs departments, combining suitable learning methods, increasing worship practices, strengthening basic religious understanding, creating engaging religious activities, and habituating Quran reading before lectures. The study's conclusion emphasizes the importance of implementing these strategies comprehensively and sustainably, with support from the entire academic community, to produce a young generation excelling in academics and possessing noble character based on Islamic values.