Engineering Tools Research Articles

Impact of Information Communication Technology Tools on Teaching and Learning of Secondary School Learners

The implementation of Information Communication Technology (ICT) has streamlined the result[1]oriented delivery of teaching and learning that has also facilitated the creation of engaging and interactive learning and enhanced the assessment. Although students currently benefit from enhanced access to diverse learning resources, peer collaboration, and self-directed learning due to technological advancements. The study is an attempt to analyze of impacts of ICT on academic and pedagogical effects on the learners of secondary school of Karachi. School learners' curiosity, ideas, and concept development matter for their future educational journey, and schools are unable to develop their competencies in the era of ICT which is a concern of all stakeholders. A survey has been used for the data collection from eight schools from all districts of Karachi. The sample has been collected randomly from the n-8 schools with N=1200 students from class 6th to 10thlevel. SPSS has been used for data analysis. The results reveal that ICT tools have not been used in teaching and learning management. Due to financial constraints, the utilization of ICT devices in classroom management is delayed or ignored. Nonetheless, inadequate electrical supply and poor internet connectivity in most of the areas significantly hinder the use of ICT devices in classrooms, compounded by the need for additional training for teachers from non-technical backgrounds. It is recommended that ICT tools should be used extensively for better learning outcomes at the school level.

Integrating Computer Science in Basic Education Curriculum: Enhancing Innovation and Sophistication for Global Competitiveness

In this study, the researcher investigated the perceptions of professional teachers in the Jolo municipality toward Integrating Computer Science into the Basic Education Curriculum (ICSBEC), including the teachers’ required capability on skills and experiences, pupils’ constructive learning and analytical thinking and technological resources, tools, and facilities to facilitate innovation and sophistication in global competitiveness. The findings showed an agreeable response with the chi-square tabular value , which means all professional teachers' perceptions of ICSBEC are about the same, dependent on the following: teachers’ capability on skills and experiences; pupils’ constructive learning and analytical thinking; and technological resources, tools, and facilities needed to meet the need for innovation and sophistication (great skills) in global competitiveness. The findings revealed strong overall support for integrating computer science into the basic educational curriculum, with a mean score of 4.447(185 or 88.94%). They indicated perceived skills and experiences needed for teachers to instruct pupils, with a mean score of 4.341 (180 or 86.54%), agreeing strongly. The constructive learning and analytical thinking skills, with a mean score of 4.515 (187 or 89.90%), strongly agreed. The availability of appropriate technological resources, tools, and facilities to prepare students for global competitiveness, with a mean score of 4.692 (195 or 93.75%), strongly agreed. These results showed positive evidence that the ICSBEC holds potential impacts in cultivating innovation and sophistication among students’ preparedness in a globalized world. The study employed a descriptive-evaluative approach. To gather quantitative data, the researcher utilized surveys distributed to 208 professional teachers and the FGD for qualitative data. The FGD was selected among the supervisors, principals and classroom advisers who possessed the information sought.

FORMATION OF RESEARCH AND COGNITIVE ACTIVITY OF STUDENTS

The article examines the issues of developing research and cognitive activity among students at the Dagestan State Pedagogical University (DSPU). In the context of rapid changes in information technologies and education, the focus is placed on the problems and methods of activating these aspects. The authors analyze the external and internal factors influencing students' cognitive activity and the motivations underlying the pursuit of knowledge and professional growth. An empirical study is presented, identifying the main obstacles to the formation of students' activity and suggesting solutions, including through the use of interactive teaching methods, case methods, project work, laboratory and practical classes, as well as brainstorming and technological tools. Purpose. The study aims to stimulate and enhance the research and cognitive activity of students at the Dagestan State Pedagogical University to improve the quality of higher education and form professionals capable of independent professional activity. Method and methodology. Application of a comprehensive approach, including the analysis of theoretical foundations of educational psychology, investigation of current interactive learning methods, and assessment of the practical application of the acquired knowledge in the educational process Results. Development and integration of interactive teaching methods, such as role-playing games, simulations, case methods, and project work, that demonstrate improved student motivation, activity, and quality of education. Scope of the results: higher education, particularly pedagogical universities and colleges, where the innovation can be integrated into teaching programs to develop critical thinking and independent research skills among future professionals.

PHÁT TRIỂN NĂNG LỰC TIN HỌC CHO HỌC SINH TRUNG HỌC PHỔ THÔNG Ở THÀNH PHỐ HỒ CHÍ MINH

Information technology competency is the ability to apply information technology and digital tools to support and improve the quality of teaching and learning in different subjects. Through teaching activities using information technology, all subjects contribute to developing this capacity. To meet the needs of developing students' information technology capabilities (mainăng lựcy the ability to use information technology) in teaching subjects, first of all, teachers are proficient in information technology skills and enhance the application of information technology in the teaching process. Teachers at high schools in Ho Chi Minh City were surveyed on the issue of developing the ability to use information technology through teaching activities in the current context. From there, propose solutions to improve the effectiveness of information technology application in teaching, improving the quality of teaching and developing information technology capacity for students in the current context of digitalization of education and training. Keywords: IT capacity; information technology; teachers; digital transformation; high school.

Identification of the effect of ripening conditions on the yield of rose hips and their processed products

Wild rose hip fruit, pulp, beverage, nectar, as well as technological methods and tools are taken as the object of research. Rose hips have a, bright red color and a rich chemical composition, which makes it a very important raw material for industry. However, insufficient research slows down this work and makes the use of raw materials inefficient. With this in mind, the aim was to study the mechanical and technological characteristics of the femur, which are considered important for industrial processing. The reflection of ripening conditions on the mechanical, physical and chemical properties of rose hips, as well as the influence of processing methods, especially hot processing, on the quality of the product has been established. Research has shown that the percentage of fruit cultivation in the Dashkasan region was the lowest, and the highest in the Gadabay region, and the Goygol region took an intermediate position. The Latin hardness of fruits grown in Dashkasan region was 6.41 N. Gadabay region with 5.56 N and Goygol region with 5.47 N. This indicator plays an important role in the storage and processing of fruits. As a result of the treatment, the amount of dry matter in fruit, pulp and beverage increased slightly, titratable acids, ascorbic acid and pH decreased. An increase in total phenolic compounds was observed during the initial heat treatment of the raw material and was noted to be much lower in the pulp and beverage. Hot treatment had a reducing effect on the amount of ascorbic acid, which is considered one of the main components of indicators in the thigh. The obtained results can be used in individual family farms and in the food industry

The Effect of Project Management System Implementation, BIM Technology, and Cloud Collaboration on Construction Project Efficiency in Riau

This study examines the impact of Project Management System (PMS) implementation, Building Information Modeling (BIM) technology, and Cloud Collaboration on construction project efficiency in Riau, Indonesia. Utilizing a quantitative research design, data were collected from 190 professionals involved in construction projects and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings reveal that all three factors—PMS implementation, BIM technology, and Cloud Collaboration—positively and significantly influence construction project efficiency. Among these, BIM technology demonstrates the strongest impact, followed by Cloud Collaboration and PMS implementation. The high R² value (0.752) indicates that these factors collectively explain a substantial portion of the variance in project efficiency. This study underscores the importance of integrating advanced technological tools and management practices to enhance project outcomes in the construction industry. The results provide practical insights for construction firms in Riau and similar regions, suggesting that the adoption of BIM, Cloud Collaboration, and PMS can lead to significant improvements in project efficiency.

Innovative Approaches to Teaching English as a Second Language: Integrating Technology for Enhanced Learning Outcomes

This study explores innovative approaches to teaching English as a Second Language (ESL) by integrating technology to enhance learning outcomes. The rapid advancement of digital tools and platforms has revolutionized the educational landscape, offering new opportunities for language acquisition. This research examines the effectiveness of various technological tools, such as language learning apps, virtual classrooms, interactive multimedia, and artificial intelligence-based tutoring systems, in improving ESL instruction. Through a comprehensive literature review and analysis of case studies, the study identifies the benefits and challenges associated with the use of technology in ESL education. It highlights how technology can foster a more engaging, interactive, and personalized learning experience, thereby improving student motivation and retention rates. Moreover, the research discusses the role of technology in providing immediate feedback, facilitating collaboration, and enabling access to authentic language resources. However, the study also acknowledges potential drawbacks, such as digital literacy gaps, accessibility issues, and the risk of over-reliance on technology. The findings suggest that while technology can significantly enhance ESL learning outcomes, it is crucial to integrate it thoughtfully and complementarily with traditional teaching methods. This study provides valuable insights for educators, policymakers, and researchers aiming to leverage technology to optimize ESL instruction and foster more effective language learning environments.

Lipid-Based Nanoparticles Fused with Natural Killer Cell Plasma Membrane Proteins for Triple-Negative Breast Cancer Therapy.

Immunotherapy combined with chemicals and genetic engineering tools is emerging as a promising strategy to treat triple-negative breast cancer (TNBC), which is more aggressive with poorer progress than other breast cancer subtypes. In this study, lipid-based nanoparticles (LNPs) possessed an NK cell-like function that could deliver tumor-specific therapeutics and inhibit tumor growth. LNPs fused with an NK cell membrane protein system (NK-LNP) have three main features: (i) hydrophilic plasmid DNA can inhibit TNBC metastasis when encapsulated within LNPs and delivered to cells; (ii) the lipid composition of LNPs, including C18 ceramide, exhibits anticancer effects; (iii) NK cell membrane proteins are immobilized on the LNP surface, enabling targeted delivery to TNBC cells. These particles facilitate the targeted delivery of HIC1 plasmid DNA and the modulation of immune cell functions. Delivered therapeutic genes can inhibit metastasis of TNBC and then induce apoptotic cell death while targeting macrophages to promote cytokine release. The anticancer effect is expected to be applied in treating various difficult-to-treat cancers with LNP fused with NK cell plasma membrane proteins, which can simultaneously deliver therapeutic chemicals and genes.

De novo-designed minibinders expand the synthetic biology sensing repertoire.

Synthetic and chimeric receptors capable of recognizing and responding to user-defined antigens have enabled "smart" therapeutics based on engineered cells. These cell engineering tools depend on antigen sensors which are most often derived from antibodies. Advances in the de novo design of proteins have enabled the design of protein binders with the potential to target epitopes with unique properties and faster production timelines compared to antibodies. Building upon our previous work combining a de novo-designed minibinder of the Spike protein of SARS-CoV-2 with the synthetic receptor synNotch (SARSNotch), we investigated whether minibinders can be readily adapted to a diversity of cell engineering tools. We show that the Spike minibinder LCB1 easily generalizes to a next-generation proteolytic receptor SNIPR that performs similarly to our previously reported SARSNotch. LCB1-SNIPR successfully enables the detection of live SARS-CoV-2, an improvement over SARSNotch which can only detect cell-expressed Spike. To test the generalizability of minibinders to diverse applications, we tested LCB1 as an antigen sensor for a chimeric antigen receptor (CAR). LCB1-CAR enabled CD8+ T cells to cytotoxically target Spike-expressing cells. We further demonstrate that two other minibinders directed against the clinically relevant epidermal growth factor receptor are able to drive CAR-dependent cytotoxicity with efficacy similar to or better than an existing antibody-based CAR. Our findings suggest that minibinders represent a novel class of antigen sensors that have the potential to dramatically expand the sensing repertoire of cell engineering tools.

Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method

BackgroundThermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure–function relationship, and is also of great interest in protein engineering and pharmaceutical design.ResultsHere we present mutDDG-SSM, a deep learning-based framework that uses the geometric representations encoded in protein structure to predict the mutation-induced protein stability changes. mutDDG-SSM consists of two parts: a graph attention network-based protein structural feature extractor that is trained with a self-supervised learning scheme using large-scale high-resolution protein structures, and an eXtreme Gradient Boosting model-based stability change predictor with an advantage of alleviating overfitting problem. The performance of mutDDG-SSM was tested on several widely-used independent datasets. Then, myoglobin and p53 were used as case studies to illustrate the effectiveness of the model in predicting protein stability changes upon mutations. Our results show that mutDDG-SSM achieved high performance in estimating the effects of mutations on protein stability. In addition, mutDDG-SSM exhibited good unbiasedness, where the prediction accuracy on the inverse mutations is as well as that on the direct mutations.ConclusionMeaningful features can be extracted from our pre-trained model to build downstream tasks and our model may serve as a valuable tool for protein engineering and drug design.

In-line indirect concentration measurement of ultralow dose API during twin-screw wet granulation based on NIR and Raman spectroscopy

Twin-screw wet granulation (TWSG) is a promising continuous alternative of pharmaceutical wet granulation. One of its benefits is that the components dissolved in the granulation liquid are distributed homogeneously in the granules. This provides an elegant way to manufacture products with ultralow drug doses. Near-infrared (NIR) and Raman spectroscopy are well-established process analytical technology (PAT) tools that can be used for the in-line monitoring of TSWG. However, their detection limit does not enable the measurement of components in the ultralow (i.e., ppm) range. In this paper, an indirect approach is presented that enables the real-time determination of the concentration of a drug in concentrations between 40 and 100 ppm by using the signal of an excipient, in this case, the polyvinylpyrrolidone (PVP). This component is also dissolved in the granulation liquid; therefore, it is distributed in the same way as the active ingredient. Results of HPLC measurements have proved that the models trained to quantify the concentration of PVP in real-time gave an accurate determination for the active ingredient as well (root mean squared error was 7.07 ppm for Raman and 5.31 ppm for NIR spectroscopy, respectively). These findings imply that it is possible to indirectly predict the concentration of ultralow dose drugs with in-line analytical techniques based on the concentration of an excipient.

Precise analysis of the static bending response of functionally graded doubly curved shallow shells via an improved finite element shear model

Doubly curved shallow shells, common in aerospace and civil engineering, pose significant challenges in predicting bending responses due to their complex geometry and material properties. Therefore, this research focused on the development of an efficient eight-node quadrilateral isoparametric element model based on a new improved first-order shear deformation theory (IFSDT) to analyze the bending deflection and stresses distribution of Functionally Graded (FG) doubly curved shallow shells. The present IFSDT obviates the necessity of a shear correction factor, which has challenges in determining for FG doubly curved shallow shells, by adopting a simpler assumption about transverse shear stresses. This assumption guarantees that the model precisely predicts the parabolic shear stresses distribution throughout the thickness of the FG shell while also meeting the requirements for free traction conditions on the top and lower surfaces of the shell. In the present analysis, five distinct types of FG doubly curved shallow shells are modeled: flat plates, spherical shells, hyperbolic parabolic shells, cylindrical shells, and elliptical paraboloid shells. A power law is employed to describe the gradual changes in material properties through the thickness direction. Numerical results for displacements and stresses are obtained for various shell types, materials, power-law factors, radii of curvature, and boundary conditions under uniform and sinusoidal loads. Comprehensive comparison and convergence studies are conducted to assess the robustness and accuracy of the proposed numerical model. This study also contributes new numerical results that are valuable for future research. Ultimately, the proposed numerical model offers a robust and straightforward tool for engineers and researchers engaged in the design and analysis of complex shell structures.

Mathematics Teachers’ Perceptions on the Use of Technological Tools in Teaching and Learning Practices in Selected Rwandan Secondary Schools

This article assessed one objective derived from an unpublished master's thesis with the title "Factors Constraining the Effective Application of Information and Communication Technology (ICT) in Teaching and Learning Mathematics: Case Study of Selected Secondary Schools in Rwanda." The objective of this study was to investigate how mathematics teachers perceive the use of technological tools in teaching and learning mathematics. Gregory's constructivist theory of perception served as the anchor for the research. A case study research design was adopted. The research focused on secondary school mathematics teachers in 10 selected Rwandan schools. Purposive sampling was employed to choose 20 mathematics teachers. Primary data was obtained through open-ended questionnaires along with semi-structured interviews, and thematic analysis was employed for data analysis. Study outcomes indicated that perceptions of mathematics teachers' of embracing technological tools are formed by their familiarity with technology, confidence in adopting it, and the help they get in incorporating it into their teaching procedures. The study concluded that teachers ought to participate in Continuous Professional Development (CPD) programs aimed at technological tools to enhance confidence and boost their integration into teaching. According to research, school leaders should ensure access to the most up-to-date technological resources and offer customized training to facilitate effective technology adoption in mathematics teaching. The study further suggested that Rwanda Basic Education Board (REB) and the National Examination and Schools Inspection Authority (NESA) should enforce extensive training programs, avail more resources in essential technological infrastructure, and boost research and best practices to encourage innovation. Additional research should broaden its context to include different perspectives, evaluate the long-term impact of technological tools on student outcomes, and assess the effectiveness of professional development programs.

Determining Which Hydrostatic Pressure Regimes Promote Osteogenesis in Human Mesenchymal Stem Cells.

Compressive loading of bone causes hydrostatic pressure changes which have been proposed as an osteogenic differentiation stimulus for mesenchymal stem cells (hMSCs). We hypothesised that hMSCs are adapted to differentiate only in response to cyclic hydrostatic pressures above critical thresholds of magnitude and frequency which correspond to physiological levels of anabolic bone loading. Using a pneumatic-hydrostatic bioreactor, we applied hydrostatic pressure regimes to human hMSCs in 3D collagen hydrogel cultures for 1h/day over 28days to determine which levels of pressure and frequency stimulated osteogenesis in vitro. Stimulation of the 3D cultures with 0-280kPa cyclic hydrostatic pressure at 1Hz resulted in up to 75% mineralisation in the hydrogel (without exogenous growth factors), whilst static culture or variations of the regime with either constant high pressure (280kPa, 0Hz), low-frequency (0.05Hz, 280kPa) or low-magnitude (70kPa, 1Hz) stimulation had no osteogenic effects (< 2% mineralisation). Nuclear translocation of YAP was observed following cyclic hydrostatic pressure in mature MLO-A5 osteoblasts but not in hMSCs, suggesting that cyclic hydrostatic pressure activates different mechanotransduction pathways in undifferentiated stem cells and committed osteoblasts. Hydrostatic pressure is a potent stimulus for differentiating MSC into highly active osteoblasts and may therefore be a versatile tool for translational cell engineering. We have demonstrated that there are minimum levels of force and frequency needed to trigger osteogenesis, i.e. a pressure 'switch', which corresponds to the physiological forces experienced by cells in their native mesenchymal niche. The mechanotransduction mechanisms underpinning these effects are the subject of further study.

The Impact of Perception-Action Training Devices on Quickness and Reaction Time in Female Volleyball Players.

The objective of this study was to examine the effect of a training program utilizing action perception technology (PAD) tools on improving the motor reaction times and neuromuscular capabilities of the upper and lower limbs compared to a traditional training program. Twenty-four female volleyball players competing in the Italian national championship were randomized into two groups of 12 athletes each: an experimental group (EG) and a control group (CG). A preliminary analysis confirmed the absence of significant differences in age and anthropometric characteristics between the groups. All the players underwent an initial battery of tests (pre-test), including Reaction Time simple Upper and Lower Limb (RTsUL and RTsLL) and Tapping Upper and Lower Limb (TUL and TLL). During a 6-week training program, the experimental group used exercises with a technological system of illuminated disks, while the control group followed the traditional training methods without advanced technology. At the end of the program, both groups were subjected to final tests (post-test). The main results show that after 6 weeks, both groups improved their performance compared to the initial tests. However, EG achieved significantly better results than CG in every test, with significant reductions in average times (ip%) of -14.9% in RTsUL (DX = -0.072 s, t = 23.2, p < 0.05, d = 6.7), -14.9% in RTsLL (DX = -0.091 s, t = 44.0, p < 0.05, d = 12.7), -10.6% in TUL (DX = -0.622 s, t = 42.0, p < 0.05, d = 12.1), and -10.7% in TLL (DX = -0.983 s, t = 43.1, p < 0.05, d = 12.4). The use of light-based perception-action technology devices in volleyball training has shown potential for significantly improving movement speed and reaction time. However, further research is needed to determine whether these improvements actually translate into enhanced overall performance in competitive contexts compared to the traditional training methods.

Adopting Artificial Intelligence to Strengthen Legal Safeguards in Blockchain Smart Contracts: A Strategy to Mitigate Fraud and Enhance Digital Transaction Security

As blockchain technology increasingly underpins digital transactions, smart contracts have emerged as a pivotal tool for automating these transactions. While smart contracts offer efficiency and security, their automation introduces significant legal challenges. Detecting and preventing fraud is a primary concern. This paper proposes a novel application of artificial intelligence (AI) to address these challenges. We will develop a machine learning model, specifically a Convolutional Neural Network (CNN), to effectively detect and mitigate fraudulent activities within smart contracts. The AI model will analyze both textual and transactional data from smart contracts to identify patterns indicative of fraud. This approach not only enhances the security of digital transactions on blockchain platforms but also informs the development of legal standards and regulatory frameworks necessary for governing these technologies. By training on a dataset of authentic and fraudulent contract examples, the proposed AI model is expected to offer high predictive accuracy, thereby supporting legal practitioners and regulators in real-time monitoring and enforcement. The ultimate goal of this project is to contribute to legal scholarship by providing a robust technological tool that aids in preventing cybercrimes associated with smart contracts, thereby laying a foundation for future legal research and development at the intersection of law, technology, and security.

Teaching Methodologies of Gross Anatomy Education for Undergraduate Physiotherapy Students: An Updated Scoping Review

Gross anatomy provides essential knowledge about the structure and function of the human body. Understanding human anatomy requires specific skills from physiotherapy students to comprehend and memorize the location and relationships of anatomical structures. This review aims to summarize the current evidence on teaching methodologies in anatomy education for undergraduate physiotherapy students. A scoping review was conducted consulting the PubMed, EBSCO, SCOPUS, and Web of Science databases. By analyzing ten studies involving over 1380 students, we identified four primary pedagogical approaches: the use of technological tools, combined traditional methods (such as dissections and radiological imaging), interprofessional education, and the innovative use of animal dissections. The findings highlight that hands-on, practical activities, especially those integrating technology (e.g., virtual reality and interactive quizzes), significantly enhance student engagement and knowledge retention. Collaborative learning through interprofessional education was found to foster a deeper understanding of anatomical concepts and improve teamwork skills, which are crucial for clinical practice. Additionally, the inclusion of traditional methods like dissections and radiological imaging, when paired with modern tools, offers a comprehensive approach that bridges theoretical knowledge with practical application. The use of animal dissections also emerged as an innovative strategy to enhance anatomical comprehension. In conclusion, the literature underscores the importance of adopting diverse and innovative teaching strategies in gross anatomy education for physiotherapy students. Such approaches not only enrich the learning experience but also ensure that students are well prepared for the demands of professional practice.

Criminology and Social Impact in The Age of Artificial Intelligence [AI

The use of technology has permeated all facets of life, and brought about both positive and negative effects. Criminology as a fields has not been left behind and criminologists are developing various technological tools, including Artificial Intelligence (AI) models to use in detecting, managing and preventing criminal activities. This is a significant step considering that criminals have also found it convenient to use technology as a tool for perpetuating their activities. This paper focused on the adoption of AI in criminology, exploring the attendant benefits of its adoption; the negative social impact of its use and interventions that should be put in place to curb the negative ramification. Some of the beneficial use discussed in the paper include predictive policing, and crime risk assessment, which aids in preventing occurrence of criminal activities. However, the use of these AI models, while beneficial to these criminological functions have presented significant social implications, which include bias and discrimination that perpetuate social stereotypes; privacy breach that lead to the victimization of innocent people; opaque decision making that lead to distrust in the output by the AI tool; and unfair distribution of employment opportunities. The paper concluded that the adoption of AI in criminology is inevitable considering the digital era in which we are currently living in. However, while the benefit of the use of these technologies are varied and welcome, there is a need for ensuring that the legal, social and ethical concerns are adequately addressed. The paper, therefore, recommended the establishment of robust regulatory framework that guide the use of the AI models by law enforcement agencies; the integration of the use of the AI tools with human oversight; the inclusion and transparency and accountability in the operationalization of the tools; collaboration amongst the stakeholders. This paper has used recent extant literature to examine the intersection between criminology and social impact with respect to the use of Artificial Intelligence (AI)

More, better feedback please: are learning analytics dashboards (LAD) the solution to a wicked problem?

There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic Dashboard (LAD), which holds the promise of a comprehensive view of student performance via partial or fully automated feedback delivered to learners in real time. The possibility of displaying performance data visually, on a single platform, so users can access and process feedback efficiently and constantly, and use this to improve their performance, is very attractive to users, educators and institutions. However, the mainstream literature tends to take an atheoretical and instrumentalist view of LADs, a view that uncritically celebrates the promise of LAD's capacity to provide a 'technical fix' to the 'wicked problem' of feedback in health professions education. This paper seeks to recast the discussion of LADs as something other than a benign material technology using the lenses of Miller and Rose's technologies of government and Barry's theory of Technological Societies, where such technical devices are also inherently agentic and political. An examination of the purpose, design and deployment of LADs from these theoretical perspectives can reveal how these educational devices shape and govern the HPE learner body in different ways, which in turn, may produce a myriad of unintended- and ironic- effects on the feedback process. In this Reflections article we wish to encourage health professions education scholars to examine the practices and consequences thereof of the ever-expanding use of LADs more deeply and with a sense of urgency.

Development and evaluation of an interactive information system in technical assistance and rural extension

The state of Espírito Santo has a wide diversification of rural activities, such as family agribusinesses and activities related to rural tourism. However, diagnosing the rural zone presents some challenges, such as the difficulty of access and location, long distances, and excessive costs, combined with the scarcity of human and financial resources inherent to public services. In this sense, it is necessary to restructure the communication and technical assistance and rural extension model established by public institutions to reinforce the trend towards the use of Information and Communication Technology (ICT) tools and the implementation of concepts such as e-government (e-Gov). In this context, we propose an interactive computational tool, focusing on diagnosing, planning, and addressing the different current demands the rural sector presents. To achieve this, we have developed a consulting and data analysis system that also employs artificial intelligence concepts, aiming to increase the efficiency and quality of public services in rural areas. The proposed system is called Agrolegal Ater Digital and includes functionalities such as registration, diagnosis, virtual library, event registration, news, and funding opportunities. The objective is to facilitate access to information for rural entrepreneurs regarding the public services offered and to increase the speed of communication with public agents. The results obtained through the conducted diagnoses are promising, with good acceptance from the test group regarding the proposed tool and the use of information technology in addressing requests in rural areas.