Researchers conducted an in-depth case study at a medium-sized farm management information system provider serving the horticulture industry, a company of roughly 120 employees that builds horticultural software on an enterprise resource planning platform extended through customizable modules, mobile applications and analytics tools. The study, which the authors describe as the first empirical investigation of process mining in farm management information system software development, combined quantitative analysis of event logs with qualitative interviews to answer three questions: how the agile development processes are actually carried out, which bottlenecks exist within them, and what causes those bottlenecks, particularly long cycle times.

Process mining works by extracting event logs from digital systems, in this case the company’s DevOps platform, where every task is automatically created after a project’s design phase and timestamped when it moves to in progress or done. These logs capture sequences of events tied to individual work items, allowing researchers to reconstruct how software development actually unfolds rather than how it is supposed to unfold on paper. The technique, described by its originator as a bridge between process science and data science, integrates business process management, optimization and analytics to uncover inefficiencies such as loops, rework and waiting times.

The researchers collected data spanning March 2020 to January 2025, then filtered it to include only product backlog items that began in 2023, the year the company’s software development process changed. After cleaning, imputation of missing timestamps with median values, and removal of outliers below ten minutes and above sixty days, the final event log contained 376 product backlog items and 2,110 tasks. The team also split the data around a key date, 15 March 2024, when the company implemented a strategy of reducing project sizes to improve development efficiency, and separated customer-driven collaborative development projects from internal maintenance and innovation work.

The control flow analysis revealed a substantial gap between the documented process and reality. Only 49 percent of product backlog items started as intended with the functional design step, with development and testing frequently serving as incorrect starting points, often because similar features allowed designs to be reused. The fitness of the desired process model to the actual event log was just 38 percent, indicating most cases were not processed exactly as expected. After correcting for data anomalies, the researchers mined a refined model with an inductive miner that achieved an average precision of 81.1 percent and a fitness of 74.9 percent. This model exposed unexpected parallelism, with technical design running alongside estimation and development alongside code review, as well as frequent loops, most notably 171 instances in the test step alone. In total, 270 different process variants were discovered, underscoring how heterogeneous real-world agile development can be.

The performance analysis produced the study’s most eye-catching number: of the median 79 days a typical development item took to complete, only 22 days involved active work. The remaining 57 days consisted of waiting time, meaning roughly 72 percent of the total cycle time was spent inactive. Flow efficiency at the company was low compared with benchmarks from earlier software engineering research, highlighting considerable opportunity for improvement by reducing delays at handover, estimation and rework stages. Over time, cycle times did fall from 109 to 79 days, and approximately 80 percent of that reduction could be attributed to lower waiting times, suggesting the project-size reduction strategy was effective.

At the level of individual process steps, code review emerged as the most critical bottleneck, showing the highest median process step duration at 16.9 days and a growing impact over the study period, driven by increases in both processing and waiting times. This finding surprised the company, since code reviews are expected to require limited effort, and interviews suggested the bottleneck correlated with delays in task completion and administration rather than the review activity itself. Automatically triggered DevOps tasks were not always followed up promptly, were often not closed when completed, and task statuses were unreliable, undermining sprint planning accuracy. Estimation and development followed as secondary bottlenecks, with estimation characterized by extremely low flow efficiency due to excessive waiting.

Comparing project types added further nuance. Customer-driven collaborative development projects achieved substantially shorter cycle times than internal projects, 48 versus 85 days, reflecting lower processing and waiting times throughout. However, technical design and development remained important bottlenecks in these customer projects, reflecting the complexity of translating customer-specific requirements into a standardized software product. The researchers also compared product backlog items with short cycle times, under 90 days, against those with long cycle times of 90 days or more, and identified three main drivers of the delays: batching of design tasks, prioritization of customer projects at the expense of internal work, and limited testing capacity, exemplified by one team with a single tester who also served as Scrum master. Notably, after the project split in March 2024, batching in functional design ceased and its median processing time plummeted from 31.3 to 0.9 days.

The qualitative interviews added context invisible in the event logs. Developers reported that ambiguities in largely text-based design documents forced time-consuming clarifications that sometimes triggered design revisions. Testing was described as highly manual, with tailored test cases often skipped initially due to time constraints in favor of predefined scenarios, which increased testing effort later and contributed to rework. Reproducing bugs depended on clear test setups, and verifying fixes manually added further workload. Communication challenges were compounded by globally distributed teams, where time zone differences limited real-time collaboration and reliance on online meetings made resolving uncertainties slower than in-person discussion would allow.

The authors caution that the findings come with limitations. The process data contained missing and inconsistent information requiring cleaning, imputation and assumptions, and the observed relationships should not be interpreted as strictly causal, since multiple organizational changes occurred during the study period. The single-company case study design also limits generalizability, and some analyses relied on relatively small subsets of data. Nevertheless, the study demonstrates that process mining, when integrated with qualitative insights from practitioners, is a powerful tool for diagnosing and improving agile software development in the agricultural domain. Faster delivery of new functionalities can help keep farm management systems aligned with the needs of farmers and growers, supporting adoption and long-term value, though the researchers note that speed gains came with increased process loops, indicating a trade-off between time efficiency and process quality that organizations must manage carefully. They suggest future work should repeat such studies with larger datasets and in other farm software companies, and position process mining not as an end in itself but as a key building block in a broader cycle of continuously discovering, analyzing and improving business processes.

Subject of Research: Application of process mining to identify bottlenecks in agile software development for farm management information systems

Article Title: Process mining for agile development of farm management information systems

Article References: Babur, Ö., Frisch, M., & Verdouw, C. (2026). Process mining for agile development of farm management information systems. Smart Agricultural Technology, 15, Article 102653. https://doi.org/10.1016/j.atech.2026.102653

Image Credits: AI Generated

DOI: 10.1016/j.atech.2026.102653

Keywords: process mining, farm management information systems, agile software development, horticulture, event logs, cycle time, waiting time, code review bottleneck, case study, business process management, DevOps, agricultural software

The motivation behind the work lies in a persistent gap between what software engineering courses teach and what the software industry actually needs. The researchers note that professors often adhere closely to traditional expository lectures and tests, leaving students unmotivated in a subject whose learning is achieved primarily through applying content to practical projects. Citing earlier work, the authors point out that a newly graduated individual typically needs between two and three years to gain professional experience in software engineering, and that companies frequently have to supplement graduates’ knowledge to promote both technical and non-technical skills. Software’s intangible and malleable nature compounds the problem, because students who can apply theory to classroom exercises still need more experience when faced with real projects and ambiguous specifications.

ConES, whose name derives from the Portuguese terms for Construction and Software Engineering, is a role-playing game built around building blocks and inspired by established systems such as GURPS and Dungeons & Dragons. Players are placed in a team hired by a king to rebuild a castle, and each participant assumes a role that mirrors a position in a real software project. The game master plays the Customer, who knows the business rules and validates deliveries, and the Manager, who removes obstacles for the team. Players choose between the Architect, who designs structures in the LeoCAD modeling tool; the Builders, who implement the design with physical blocks; and the Tester, who monitors construction and fills out a compliance checklist comparing what was built against what was requested.

The game’s mechanics translate software engineering practices into explicit, auditable rules. Each player fills out a character sheet distributing attribute points across three categories: soft skills, hard skills, and scope mastery. Action cards, usable once per turn and tied to specific roles, grant benefits if the player passes a skill test, a dice roll in which the action succeeds when the result is less than or equal to the sum of the attributes involved. Demand cards carry the Customer’s requirements together with acceptance criteria, while event cards represent random requirement changes that force teams to adjust mid-turn. A Customer Requested Changes Sheet tracks corrections across rounds. The researchers mapped the game’s rules to the Software Engineering Body of Knowledge, so that demand cards operationalize requirements engineering, LeoCAD models simulate architectural decisions, the compliance checklist operationalizes verification, and physical construction operationalizes implementation.

A full match unfolds across five phases: Introduction and Character Creation, Turn Planning, Turn Execution, Demand Delivery, and Retrospective. In the Retrospective phase, players gain an experience point and reflect on difficulties and strategies for future turns, a structure the authors link to Kolb’s Experiential Learning Cycle. Before the classroom application, the game went through a systematic literature mapping and the validation of two prototypes. For the case study itself, the Player’s Manual was distributed a week in advance through Google Classroom, and the session was planned under the guidance of two software engineering professors, with a game researcher conducting the play.

The classroom session began an hour late because not enough students had arrived at the scheduled start time, a delay the authors acknowledge may have negatively affected the study by forcing an early finish. Once underway, the 20 students were divided into four teams of five, each with one Architect, three Builders, and one Tester. The narrative placed them at Medieval Solutions, an organization hired by a king whose castle had been attacked by orcs. The first demand was a wall, built under a 10-minute timer, and none of the teams met all the requirements on their first attempt, which the professors had anticipated given the players’ inexperience. By the second round, involving a moat, teams began using action cards effectively: one Builder from Team A passed a skill test to access four additional blocks, and Team B’s Tester passed a test allowing him to assist a Builder.

The third and fourth rounds introduced event cards and a tower demand, and the professors observed behaviors that echoed real project dynamics. Teams A and D tried to discard an unexpected event card through skill tests; Team D’s Architect succeeded while Team A’s failed, forcing that team to continue with the disruption. Team C, having missed the moat criterion of a distinct color, prioritized correcting that fault before starting the tower. As the timer ran down, players increasingly abandoned their defined roles, with Builders, Architects, and Testers overlapping in function. By the final evaluation, all teams built their structures satisfactorily, and one team even met the tower’s window criterion using unexpected blocks, suggesting that success improved as players gained experience.

The quantitative results were detailed and consistently favorable. In the background and motivation questionnaire, the three knowledge areas of architecture, construction, and testing were rated important, with means between 3.60 and 3.70, while motivation to learn software engineering showed the highest dispersion, with a standard deviation of 1.00. In the feedback questionnaire, the nine items obtained means between 3.25 and 3.95, and all nine were significantly above the scale midpoint with p values below 0.01 and effect sizes between 0.71 and 1.00. The Friedman test confirmed the differences among items were informative rather than random. The fun and challenge of the dynamics rated highest, with 95 percent of participants giving the top score, while the amount of building blocks ranked lowest, with 80 percent positive ratings. Notably, the three lowest-rated items concerned time constraints, block quantity, and complexity level, suggesting that reservations targeted the operational conditions of the session rather than the game’s design. The game master’s presence earned a mean of 3.75, and no participant produced a predominantly negative evaluation.

The collective SWOT analysis revealed both strengths and friction points. Participants praised the game’s playful presentation of the software development process, its encouragement of creativity, and one noted that its phases resembled the steps of the Agile Scrum methodology, while another described the character sheet as a form of self-assessment. Weaknesses centered on communication failures with the Customer and Manager, the absence of a planning stage, the short 10-minute time limit, and the isolation of Testers and Architects during rushed final rounds. The study also documented a revealing divergence: some participants asked for reduced complexity while others requested more complex challenges, a pattern with a standard deviation of 0.82 on the complexity item. The authors connect this to gamification research showing that player profiles, such as the Bartle archetypes or the Hexad typology, moderate responses to game mechanics, though they emphasize that the study measured Kolb learning styles, not player profiles, and could not distinguish between experience-based and motivation-based explanations for the divergence.

The authors are explicit about the study’s limits. The instruments were ad hoc questionnaires and a SWOT analysis rather than validated scales such as the System Usability Scale or the Intrinsic Motivation Inventory; no objective learning measures like pre- and post-knowledge tests were collected; the sample of 20 students from a single institution was small and homogeneous; and the anonymous questionnaires could not be linked across instruments. A controlled experiment was deliberately avoided because randomly withholding the activity from part of a single class raised pedagogical objections and would have yielded subgroups too small for statistical power. The findings therefore indicate the direction and consistency of participant perceptions, not generalizable estimates of learning gains. Future work outlined by the team includes replication across multiple institutions, adoption of validated scales, objective learning measures, incorporation of a player-profile instrument such as the Hexad scale, and extension of ConES to other software engineering knowledge areas, building on evidence that the game’s cooperative, face-to-face format surfaces difficulties, such as role isolation and communication breakdowns under time pressure, that individually mediated educational games cannot observe.

Subject of Research: A role-playing game for teaching software product construction in software engineering education

Article Title: A case study on the application of a role playing game to support the teaching of software product construction

Article References: dos Santos Guerra, A., Oliveira, S. R. B., & Furtado, J. C. C. (2026). A case study on the application of a role playing game to support the teaching of software product construction. Discover Education, 5(1), Article 1220. https://doi.org/10.1007/s44217-026-02258-3

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02258-3

Keywords: software engineering education, role-playing game, ConES, gamification, case study, software construction, Lego building blocks, Kolb learning styles, SWOT analysis, computer science students, Brazil, Discover Education

To track change over time, they applied the McKinsey organisational capacity assessment grid across seven dimensions, following how the company's capabilities evolved during the study window. This approach allowed the team to document business model innovation activities alongside observed changes in organisational capacity. The findings show that business model innovation progressed along four identifiable lines: cognitive search, creation, experiential learning and experimentation.

Alongside this process, the company enhanced capabilities in six areas captured by the assessment grid: strategic, operational, human-resource, infrastructural, structural and cultural. Competitive positioning at the case level was achieved by embedding eco-innovation into the business through five mechanisms: recycling, waste utilisation, product diversification, resource efficiency and circular practices. The study identifies these practices as the basis of the company's sustainable competitive advantage, documenting how recycled materials and waste streams were incorporated into its operations and product range.

Beyond firm-level outcomes, the study documents socio-economic effects in the surrounding rural community. These include rural employment, participation of women in the workforce, skill development, community participation and environmental activities. The authors present these as case-level observations, noting that the evidence base is a single enterprise, so the findings are illustrative rather than statistically generalisable across the rural sector or other emerging markets.

Subject of Research: Eco-innovation, business model innovation and organisational capacity development in a rural emerging-market enterprise

Article Title: Eco-innovation and sustainable rural transformation in emerging markets

Article References: V K, R., Mohan, B. C., Pai, M. A., & Karanth, B. (2026). Eco-innovation and sustainable rural transformation in emerging markets. Discover Sustainability. https://doi.org/10.1007/s43621-026-05039-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-05039-y

Keywords: eco-innovation, business model innovation, organisational capacity, rural development, emerging markets, circular economy, case study, sustainability, qualitative research, waste utilisation, sustainable, rural

Researchers analyzed three official documents from the Pró-Atleta 2025 process: the consolidated call for applications, the results announcement and the first-round enrollment notice. They also sought information from 69 Brazilian federal universities about procedures for admitting high-performance athletes. Of those institutions, 66 reported having no such procedure, one did not respond, and two—UFMS and the Universidade Federal de Santa Maria—reported having athlete-specific admission processes. UFMS alone met the study’s three inclusion criteria: its call included para-sports, its results listed candidates’ scores, and it identified participants’ levels of competition. Because the analysis used publicly available documents without identifiable personal data, it was exempt from research-ethics review.

UFMS introduced Pró-Atleta in 2023 as an experimental and temporary means of expanding access to undergraduate education on the basis of athletic achievement. The first selection took place in December 2023, with undergraduate study beginning in 2024. No Brazilian federal law nationally guarantees reserved university places for high-performance athletes, but university autonomy permits institutions to establish admissions procedures compatible with federal law. Pró-Atleta converted recent competition results into a points system. Bronze, silver and gold medals in state competitions carried 25, 40 and 50 points, respectively; national medals carried 75, 120 and 150 points; and international medals carried 225, 360 and 450 points.

The 2025 call provided one place for each program at each administrative unit, producing 103 openings across 53 undergraduate programs. These comprised 37 bachelor’s degree programs, 14 teacher-education programs and two higher-education technology programs. Medicine, law and dentistry did not offer places. Forty-nine openings were located at Cidade Universitária in Campo Grande, while the remaining 54 were distributed across nine campuses in Mato Grosso do Sul’s interior. Applicants could select a first and second program. Among 57 submissions, 37 were validated; 34 of those applicants placed a Campo Grande program first, and 28 placed one second. Of the validated group, 22 were admitted, producing an admission rate of 59.46 percent.

Academic preferences were concentrated in fields closely related to sport. Physical education accounted for 24.32 percent of first choices and physical therapy for 21.62 percent, together representing 45.94 percent of validated applications. As second choices, physical education, physical therapy, nutrition, nursing and psychology each received 10.81 percent of selections. Considering both preferences, 33 of the 53 programs attracted at least one application: 22 were bachelor’s degrees, nine were teacher-education programs and two were higher-education technology programs. The results show broad access to different subject areas but also concentration in physical education and physical therapy, along with no first-choice applications for nearly half of the offered programs.

Points among validated applicants ranged from 50 to 4,500. The most common intervals were 100–199 points, representing 16.21 percent of validated applications; 300–399 points, with 13.51 percent; and 1,200–1,299 points, with 10.81 percent. The 22 athletes admitted in the first round had the same minimum and maximum scores. State-level competitors accounted for 41 percent of validated applicants, while national-level and state-level competitors each represented 36.5 percent of admitted athletes. International competitors were a small minority of the admitted group. The results therefore document substantial participation by athletes already competing at state and national levels, without establishing whether the program reached a representative distribution of athletes across every competitive level.

Admissions were divided between general places and places reserved for groups defined by Brazilian law. Of the 22 first-round admissions, 13 used general places and nine used reserved places, meaning 40.9 percent of admitted athletes entered through reserved categories. One category for candidates who completed high school in public schools, regardless of income, filled all seven of its available places. Other categories were filled at lower rates or left vacant. The results also included high-scoring applicants who did not receive places, including candidates with 1,215, 1,080, 730 and 450 points in general competition and candidates with 2,475, 1,290, 575 and 465 points in reserved categories. Thus, fewer applications than openings at the program level did not mean weak competition within every course, campus or admission track.

Pró-Atleta places successful applicants within the regular student body of a Brazilian federal university rather than making continued enrollment depend on renewed athletic performance. The authors state that, once admitted and enrolled, students may continue their degrees and cannot be dismissed because of poor sporting results, injury or retirement. The program also retains the admission categories established by Brazil’s affirmative-action framework, allowing athletic achievement to operate alongside considerations of race, income, disability and public-school attendance. The case study further notes that the 2025 call excluded former athletes whose results fell outside the three-year scoring window, identifying retirement as a limitation of the program’s eligibility rules.

The study was limited to documentary evidence from UFMS and a single 2025 admission cycle, without interviews with athletes or university administrators. It therefore could not assess students’ academic progress, continued sporting performance, reasons for applying or experiences of the admissions process. Other documented limitations include low competition for many places, concentrated interest in physical education and physical therapy, limited demand for interior campuses, and the exclusion of former athletes. The authors suggest broader outreach to federations, clubs and schools, review of allocations in the most requested programs, refinements intended to reduce differences among programs and cities, and mechanisms for recognizing retired athletes. They also recommend research covering more admissions cycles, the program at the Universidade Federal de Santa Maria, and the academic and athletic performance of students admitted through Pró-Atleta. The 2025 results provide a bounded account of how one new policy operated, without establishing its long-term reach or benefits.

Subject of Research: Evaluation of the 2025 Pró-Atleta athlete-admissions process at the Universidade Federal de Mato Grosso do Sul.

Article Title: Admission requirements for athletes in higher education: analysis by Pró-Atleta at the Universidade Federal de Mato Grosso do Sul, Brazil

Article References: Silva, J. V. P. D., & Albuquerque, A. C. D. (2026). Admission requirements for athletes in higher education: analysis by Pró-Atleta at the Universidade Federal de Mato Grosso do Sul, Brazil. Frontiers in Sports and Active Living, 8, Article 1955933. https://doi.org/10.3389/fspor.2026.1955933

Image Credits: AI Generated

DOI: 10.3389/fspor.2026.1955933

Keywords: athlete admissions, higher education, UFMS, Pró-Atleta, dual careers, Brazilian universities, public policy, affirmative action, sports policy, case study, Admission, requirements

The researchers built a kinetic-based quasi-equilibrium infection-and-recovery model with data-driven components and control events. A Sugeno-type fuzzy inference system estimated per-capita vector density from climatic variables and past dengue incidence, while a Gamma distribution represented human contact patterns. Weekly reported dengue cases, rainfall, temperature and humidity were incorporated with specified time lags for model variables. The model also represented two socio-economic events: the large-scale cleaning and fogging campaign conducted in 2018 following the 2017 outbreak, and reduced mobility during COVID-19 restrictions in 2020. The abstract does not provide enough methodological detail to determine whether mobility itself was entered with a time lag.

In the case study using data from the CMC area of Sri Lanka, simulated dengue incidence patterns closely matched the reported data across 2016–2024, with the stated accuracy levels varying by year. Comparisons with a traditional kinetic susceptible-infected-recovered model showed negligible differences in estimated infected-host populations. The researchers interpreted this as qualitative and quantitative agreement between the two modeling approaches. The model also reflected seasonal trends associated with climatic data and social behavior, according to the abstract.

The study presents a framework for combining climatic, vector-related and human-behavioral information in dengue transmission modeling. Its authors propose that such integration could assist transmission prediction and planning of control strategies, particularly where vaccine coverage is limited. That application remains a proposed use rather than evidence of improved real-world control outcomes. The reported evaluation is geographically bounded to one Sri Lankan area, and the abstract does not describe validation in other locations, uncertainty intervals, performance against additional modeling methods or the effects of individual interventions separately from the combined model. It also identifies more detailed information on human movement and behavior as a possible direction for improving predictive accuracy.

Subject of Research: Kinetic modeling of dengue transmission using climate, incidence and socio-economic data

Article Title: A robust kinetic theory-based model for dengue transmission integrating climatic and socio-economic dynamics

Article References: Hansika, S., Erandi, H., Perera, S., Attanayake, C., & Amadi, M. (2026). A robust kinetic theory-based model for dengue transmission integrating climatic and socio-economic dynamics. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14492-z

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14492-z

Keywords: dengue transmission, kinetic model, mathematical modeling, Sri Lanka, climate variables, vector density, case study, COVID-19 mobility, vector control, robust, kinetic, theory-based

The scale of the problem they set out to investigate is striking. Drawing on data from UN Women and global studies, the authors note that 58 percent of women and girls have experienced some form of technology-facilitated violence, a figure expected to rise as connectivity expands. Major platforms such as Facebook, X and Instagram have reached levels of toxicity that are difficult to ignore, and the abuse women face follows recurring gendered patterns: sexual harassment, body shaming, doxing, cyberstalking, AI-generated fake intimate images and threats of sexual violence, all designed to humiliate, silence or intimidate by attacking identity rather than argument.

What makes this study different is its method. Rather than surveying victims or cataloguing harm, the researchers used a qualitative multiple-case study design grounded in feminist standpoint theory, analyzing 127 publicly available documents, including social media posts, press statements, interviews and news coverage, relating to three women whose encounters with online abuse are widely documented: media critic Anita Sarkeesian, South African investigative journalist Ferial Haffajee, and celebrity media personality Bonang Matheba. The cases were selected purposively to represent different professional contexts, levels of visibility and sociocultural pressures, and materials were organized chronologically to trace how harassment unfolded and how responses evolved over time.

The three cases reveal distinct but overlapping forms of harm. Sarkeesian, whose feminist critique of video games triggered the coordinated Gamergate harassment campaign, faced death threats, doxing attempts and what she described as aggressive dogpiles of thousands of voices trying to silence feminist perspectives, forcing canceled appearances and heightened security. Haffajee endured gendered and racist attacks tied to her reporting on state capture and corruption, describing how the abuse had a chilling effect because the phone has become an appendage of the body, so the attacks go right into you. Matheba, meanwhile, was targeted through viral defamation, including a false drug allegation that became the subject of a successful lawsuit, showing how quickly misinformation can threaten a commercially built reputation.

Across all three cases, the initial phase of abuse produced genuine psychological cost: fear, emotional distress, reputational pressure and self-doubt. The researchers are careful not to minimize this. Online harassment shares the defining criteria of traditional violence, deliberate intent, power imbalance and repetition, and its effects extend to mental health, physical safety and social participation. Yet the study’s central insight is that this phase of victimhood was not permanent. The harm created a need to respond, and that need became the starting point for reflection and strategic adjustment.

The responses the authors documented were strikingly practical rather than confrontational. Sarkeesian continued producing educational content and public advocacy while deliberately disengaging from her most persistent harassers, transforming personal attacks into a broader debate about gender inequality in gaming. Haffajee kept publishing investigative journalism, corrected misinformation selectively and spoke publicly about online misogyny as a rising threat to media freedom, noting that blocking abuse had simply become part of her daily routine. Matheba relied on legal action, official clarification statements and tightly controlled communication to stabilize her reputation and protect commercial partnerships.

From these patterns the researchers build a conceptual framework with four dimensions: experiences of online abuse, power structures that reproduce offline patriarchy on digital platforms, resistance and coping strategies, and digital agency. Their key theoretical contribution is the argument that victimhood and agency are not opposites. A woman can experience digital harm and still act with resilience; she can feel fear and still speak, retreat in one moment and re-engage in the next. Agency, in this framing, is relational and strategic, expressed through knowing when to speak, when to log off, how to manage visibility and when to call on legal or institutional support.

The study also engages a sharp critique circulating in resilience scholarship: that emphasizing individual resilience can quietly shift the burden of coping onto victims while systemic problems go unaddressed. The authors acknowledge this tension explicitly, arguing that resilience must not become an excuse to demand adaptation from women in hostile environments. Digital resilience, they insist, is relational, growing out of supportive networks, professional institutions and community solidarity, and it fails where platform moderation is weak and institutional responses inadequate.

The practical implications are concrete. The researchers call for faster, more transparent platform reporting systems, more consistent content moderation of gendered attacks, digital literacy programs that teach privacy management and safe participation, and stronger legal accountability for gender-based cyber violence. They also flag limitations: three high-profile cases cannot represent all women, and publicly available data cannot capture private emotional consequences, so future research should include less visible women and combine documentary analysis with interviews.

Ultimately, the study reframes women’s digital experiences as more than victim stories. The three women analyzed did not simply endure harassment or withdraw from public life; they renegotiated the terms of their participation, set boundaries, leveraged support and sustained their voices in spaces explicitly designed to silence them. Understanding that journey, the authors conclude, is essential to building digital environments where women can participate safely, keep their dignity intact and remain visible and influential on their own terms.

Subject of Research: How women transition from online abuse victimhood to digital resilience and agency

Article Title: From victimhood to agency: women’s digital resilience journeys

Article References: Magadani, L., & Phahlane, M. (2026). From victimhood to agency: women’s digital resilience journeys. Frontiers in Sociology, 11, Article 1849427. https://doi.org/10.3389/fsoc.2026.1849427

Image Credits: AI Generated

DOI: 10.3389/fsoc.2026.1849427

Keywords: online abuse, digital resilience, women's agency, feminist theory, cyber harassment, social media, Gamergate, gender-based violence, case study, content moderation, digital safety, misogyny

Functional movement disorder (FMD) is a subtype of functional neurological disorder characterized by abnormal movements, including functional tremors, dystonia, gait disturbances, and parkinsonism, that are not explained by structural damage or another movement disorder. Historically dismissed as purely psychological, FMD is increasingly recognized as a genuine disorder of brain network function. Recent neuroimaging studies have revealed altered connectivity within motor networks, particularly involving the SMA and primary motor cortex, suggesting that the condition reflects measurable changes in how brain regions communicate rather than imagined symptoms.

The patient’s story began when he developed progressive tremors and co-contraction of his arms and legs that interfered with daily activities. Despite extensive testing, including brain MRI, blood work, and nerve conduction studies, no structural cause could be identified. He also experienced new-onset migraines, recurrent fevers, and hypertension, complicating the diagnostic picture. After years of unsuccessful treatments, he was referred to the researchers’ hospital for evaluation of rTMS therapy.

Before stimulation, the team recorded resting-state EEG under eyes-closed conditions and analyzed functional connectivity between electrode sites. They found relatively prominent theta activity at the Cz electrode, overlying the medial frontal cortex, together with altered alpha synchronization patterns across frontal and parietal regions. The researchers interpreted these findings as evidence of hyperexcitability within medial motor regions, consistent with the known role of the SMA in generating functional tremors. Based on this EEG profile and the established literature, they selected the SMA as the stimulation target.

The team applied low-frequency rTMS, delivering 1,200 pulses per session at 90% of the resting motor threshold, over the SMA. Low-frequency stimulation is thought to suppress cortical excitability, potentially normalizing the hyperactive medial motor circuits implicated in functional tremors. The patient underwent ten sessions over two weeks, followed by staged rehabilitation that progressed from relaxation and gentle passive movements to active task-oriented exercises incorporating video feedback of his own movements.

The results were striking. By the end of treatment, the patient’s tremors during bilateral arm elevation had diminished noticeably, and he could perform daily activities with greater ease. Standardized assessments confirmed improvements in the FMD rating scale and activities of daily living. Perhaps most remarkably, follow-up EEG revealed normalization of the previously altered connectivity patterns, with reduced relative prominence of the Cz theta activity and more balanced alpha synchronization across frontal and parietal sites. The brain’s communication patterns appeared to shift toward normal as movements improved.

The researchers emphasize that this case illustrates the potential of EEG-guided neuromodulation for FMD. Rather than applying stimulation blindly, the team used the patient’s own brain activity to identify hyperexcitable regions and select an individualized target. This approach aligns with the emerging concept of brain-state-dependent stimulation, in which the patient’s neural profile determines the intervention. The staged rehabilitation that followed may have consolidated the gains by retraining motor circuits through repeated, feedback-enhanced practice.

However, the researchers caution that this is a single case study and that the tremor recurrence at follow-up highlights the need for longer-term strategies. The patient’s tremors returned within weeks of discharge, suggesting that the neural changes induced by stimulation may require maintenance sessions or ongoing rehabilitation to sustain. The researchers also note that the autonomic symptoms, including fevers and blood pressure fluctuations, remained unexplained and may reflect broader network dysfunction beyond the motor system.

Despite these limitations, the case offers a compelling glimpse of the future of FMD treatment. As neuroimaging and EEG analysis become more sophisticated, clinicians may increasingly use patients’ own brain activity to guide individualized neuromodulation, moving beyond the one-size-fits-all approaches that have dominated the field. For a condition long dismissed as untreatable or imagined, the ability to visualize and reshape brain network function represents a genuine breakthrough, offering hope to patients whose bodies have betrayed them for years.

The epidemiological profile of FMD helps place this case in context. With an annual incidence of roughly 4 to 5 per 100,000 people and a prevalence near 50 per 100,000, the condition is far from rare, and it is frequently encountered in general neurology clinics and pediatric departments. Functional tremor, the subtype seen in this patient, is the most common presentation. Although approximately 70 percent of affected individuals are women, with a mean age at onset of around 40 years, the proportion of male patients rises with age, which is relevant when considering cases like this one involving a man in his late thirties.

The precipitating event described here also fits a well-recognized pattern. Patients with FMD often report psychological stressors or physical trauma, such as motor vehicle accidents, in the period preceding symptom onset. In this instance, a load weighing more than 100 kilograms fell toward the patient at work, twisting his body forcibly to the left and triggering severe neck and back pain. Structural workup, including lumbar MRI showing a sacral bone contusion and disc herniation, could not account for the generalized movement disorder that emerged, and the subsequent development of tremors, abnormal sensations, fever, and hypertension one month after injury illustrates how functional symptoms can layer onto genuine tissue injury, complicating diagnosis and delaying recognition.

The autonomic dimension of this case deserves particular attention. Beyond motor symptoms, FMD has been associated with alterations in autonomic and endocrine function, and recent studies have reported diminished vagal tone in these patients, suggesting altered autonomic regulation and reduced stress resilience. The patient’s unexplained hypertension, recurrent fevers of 37 to 38 degrees Celsius, and new-onset migraine prompted an unusually thorough differential workup, including serum catecholamine measurements to exclude pheochromocytoma, autoimmune screening, head-up tilt testing, and sympathetic skin response testing. Notably, heart rate variability was not assessed, which the authors acknowledge as a limitation given that reduced vagal tone has been documented in FMD populations and might have provided a physiological correlate of the autonomic instability observed.

The neuroimaging literature offers a framework for understanding why the supplementary motor area was chosen as the stimulation target. In patients with functional tremor, prior multimodal imaging work has described increased activity within a motor-limbic network involving the anterior cingulate cortex and paracingulate cortex, alongside reduced activation of the right temporoparietal junction. This reduced temporoparietal activation is thought to contribute to an impaired sense of agency, the subjective experience that movements occur outside one’s voluntary control, which is a hallmark complaint in FMD. Increased resting-state regional cerebral blood flow has also been reported in the left inferior frontal gyrus and insular cortex. These findings collectively portray FMD as a disorder of distributed network dynamics rather than a focal lesion, providing a rationale for using connectivity measures to guide intervention.

The EEG methodology used in the case reflects this network perspective. Resting-state recordings were acquired with a standard clinical amplifier using the international 10-20 electrode system, with averaged auricular references, under eyes-closed conditions. After excluding artifact-contaminated segments, the team analyzed a continuous five-minute segment using power spectral density estimation via Welch’s method and the weighted phase lag index, a connectivity measure that is relatively robust to volume conduction artifacts. Analyses were performed with established open-source Python libraries, and spectral estimates were normalized across the frequency range to allow comparison between electrodes. This combination of spectral and connectivity metrics allowed the team to characterize both local oscillatory abnormalities and the coordination between distant regions, which is precisely the kind of information needed to select a neuromodulation target in a network disorder.

The rehabilitation component of the intervention is also grounded in established principles. Staged rehabilitation that progresses from relaxation and passive movement toward active, task-oriented exercise with visual feedback exploits the same neuroplastic mechanisms that underlie motor learning in other neurological conditions. Visual feedback of one’s own movement is particularly relevant in FMD, where restoring the sense of agency over voluntary action is considered a key therapeutic goal. The combination of neuromodulation to reduce abnormal excitability and structured practice to reinforce adaptive motor patterns represents a theoretically coherent pairing, even though the relative contributions of each component cannot be disentangled in a single case.

The recurrence of tremors after discharge underscores a broader challenge in FMD management. Symptom relapse following short courses of intervention is common across treatment modalities, and the finding that gains eroded within weeks suggests that network changes induced by stimulation may be functionally reversible rather than structurally consolidated. Maintenance stimulation schedules, extended rehabilitation, or periodic reassessment with EEG to retune targets may be needed to sustain benefit. The authors’ decision to keep all regularly scheduled medications, including those for dilated cardiomyopathy and migraine, at unchanged doses throughout the treatment period strengthens the attribution of motor improvements to the neuromodulation and rehabilitation program rather than to pharmacological changes.

Ultimately, this case adds to a growing body of literature suggesting that FMD, long dismissed as untreatable or imagined, can be approached with the same objective, mechanism-targeted tools applied to other neurological disorders. The convergence of EEG-based network analysis, rational target selection, and feedback-enhanced rehabilitation offers a template for future controlled studies, which will be essential to determine whether such individualized protocols can deliver durable benefit across the broader FMD population.

Subject of Research: Case Report: Electroencephalography-informed low-frequency repetitive transcranial magnetic stimulation targeting the supplementary motor area in severe functional movement disorder

Article Title: Case Report: Electroencephalography-informed low-frequency repetitive transcranial magnetic stimulation targeting the supplementary motor area in severe functional movement disorder

Article References: Takahashi, C., Asahi, T., Kanda, M., Ohta, Y., & Matsushita, I. (2026). Case Report: Electroencephalography-informed low-frequency repetitive transcranial magnetic stimulation targeting the supplementary motor area in severe functional movement disorder. Frontiers in Psychiatry, 17, Article 1959751. https://doi.org/10.3389/fpsyt.2026.1959751

Image Credits: AI Generated

DOI: 10.3389/fpsyt.2026.1959751

Keywords: functional movement disorder, transcranial magnetic stimulation, EEG, supplementary motor area, neuromodulation, brain connectivity, rehabilitation, case study, Case, Report, Electroencephalography-informed, low-frequency

The study, titled ‘Design and Implementation of Personalized Teacher Professional Development: A Case of an NGO-Based School System in Pakistan’, examines a professional development model implemented across 25 NGO-based schools in two regions of the country. Rather than delivering identical training packages to all teachers regardless of their experience, subject area, or classroom context, the programme began by identifying what individual teachers actually needed to learn. On the basis of those identified needs, targeted audio-visual modules were developed, covering areas such as formative assessment, classroom questioning techniques, and differentiated instruction. Teachers then accessed these modules through audio-visual studios established within the schools themselves, a design choice that placed professional learning resources physically close to the point of practice.

The technical architecture of the model is worth examining because it departs from the mobile-first or fully online formats that dominate discussions of digital education. Instead of relying on personal devices and internet streaming, the programme created shared, school-based AV studios where teachers could watch and work with audio-visual learning resources. This design acknowledged the infrastructure realities of resource-constrained settings: connectivity can be intermittent, electricity supply can be unreliable, and not every teacher owns a suitable device. By concentrating the technology in a dedicated school space, the model gave teachers a reliable venue for self-paced learning while also creating a natural site for peer collaboration. Teachers could revisit materials as often as they needed, a flexibility that conventional workshops, by their very nature, cannot offer.

Crucially, the digital resources were never intended to stand alone. The programme combined self-paced engagement with audio-visual content against a backdrop of practice, reflection, peer feedback, and mentoring. School-level facilitators, including school leaders and programme implementation personnel, played an active role in helping teachers connect what they encountered in the modules with their everyday classroom routines. This pairing of asynchronous digital content with synchronous human support reflects a growing consensus in the professional development literature: sustained, practice-embedded learning tends to outperform isolated training events, and the presence of a knowledgeable other can make the difference between passive consumption of content and genuine change in instructional behaviour.

To understand how the model worked in practice, the researchers adopted a case study design, interviewing key school-level stakeholders including programme developers, implementers, school leaders, and teachers. Programme documents were also examined in order to reconstruct the processes of design and implementation and to capture participants’ experiences of the model. This methodological choice matters. Case studies cannot establish causal effects, and the authors are explicit on this point: the study does not claim to demonstrate that the programme improved teaching quality in any measurable, causal sense. What it does provide is rich evidence of how a personalised, technology-supported approach to professional development can actually be designed and implemented under resource constraints, and of the conditions required to keep such professional learning alive over time.

The findings from the interviews paint a encouraging picture of teacher engagement. Teachers reported using more interactive instructional strategies in their classrooms, adjusting their questioning practices, and changing the pacing of their lessons. They described returning independently to the audio-visual materials to revisit concepts, and they spoke of becoming more reflective about their own teaching. These are precisely the kinds of behavioural shifts that professional development programmes aspire to produce but often fail to document. Equally significant was the role attributed to the implementers, who helped teachers interpret the digital content and translate it into classroom-appropriate actions. Without that interpretive layer, the study suggests, the modules risked remaining abstract resources rather than becoming catalysts for changed practice.

The challenges teachers encountered were neither trivial nor surprising. Internet connectivity was inconsistent, electricity supply was unreliable, access to equipment was uneven, and some teachers faced long travel to reach schools equipped with AV studios. These obstacles are endemic to technology-based interventions in developing contexts, and the study does not minimise them. Yet the most important insight to emerge from teachers’ experiences was not about infrastructure at all. It was that the technology became meaningful only when it was combined with dialogic professional learning, that is, with interaction among colleagues and with mentors. The technology itself was not the transformative element. Its integration with professional dialogue, mentoring, and collaborative reflection was what strengthened teachers’ engagement and sustained their learning.

This conclusion carries a caution that extends well beyond Pakistan. Enthusiasm for digital solutions in education frequently outruns the evidence, and funders and policymakers are often tempted to equate the provision of devices and content with the achievement of professional growth. The study pushes back against that equation directly, arguing that technology alone is unlikely to transform teacher professional development. Its potential, the authors contend, is far greater when it is embedded within a human-centred system of professional support. The practical implication is a question of balance: digital resources can extend reach, enable self-pacing, and allow repeated access to content, but they require sustained human support to be interpreted, contextualised, and converted into durable changes in teaching.

The wider relevance of the findings lies in what the study offers to other education systems searching for alternatives to one-off, standardised teacher training. The authors are careful not to suggest that the Pakistani model can simply be transplanted elsewhere. Instead, they argue that its underlying principles are what merit adaptation: identifying teachers’ learning needs before designing provision, providing flexible access to professional learning resources, supporting structured reflection, and maintaining local mentoring relationships. These principles, they suggest, could be adapted to different institutional and resource contexts, whether in other developing education systems or in settings where conventional training has similarly failed to engage teachers meaningfully. The emphasis on principles over procedures is a deliberate methodological stance, recognising that the specific configuration of studios, modules, and facilitators emerged from a particular set of local conditions.

The study closes with a sober assessment of what expansion would require. Education systems in developing contexts, the authors conclude, are fully capable of generating contextually grounded approaches to teacher development rather than importing models designed elsewhere. But successful scaling is not automatic. It demands careful planning, reliable infrastructure, continued mentoring, institutional commitment, and sustained investment in both people and technology. In an era when artificial intelligence platforms and mobile learning apps promise to personalise education at scale, this case study from 25 Pakistani schools offers a grounded counterpoint: personalisation in professional learning is less about the sophistication of the technology than about the quality of the human relationships and institutional structures that surround it. For policymakers, programme designers, and researchers interested in teacher development under resource constraints, the message is clear. Build the studios, yes, but build the mentoring around them, because it is the combination, not the hardware, that changes how teachers teach.

Subject of Research: Personalised, technology-supported teacher professional development in resource-constrained Pakistani schools

Article Title: A study from Pakistan offers contextual insights into Personalized Teacher Professional Development

Article References: A study from Pakistan offers contextual insights into Personalized Teacher Professional Development. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: teacher professional development, Pakistan, audio-visual studios, personalised learning, mentoring, ECNU Review of Education, case study, education technology, resource-constrained education, NGO schools, formative assessment, teacher training

The study, published in Discover Education by Alexander M. Sidorkin, examined a single 16-week semester of a course in child and adolescent development. Thirty-six students enrolled, most of them juniors and seniors at a regional public university serving a substantial Hispanic-serving and first-generation population. Most arrived with no prior coursework in qualitative research, no familiarity with academic publishing conventions, and little experience writing extended scholarly manuscripts. Yet the course required each of them to produce a full-length qualitative research manuscript of at least 5,000 words and to submit it to a peer-reviewed journal, with confirmation of submission as part of the final assignment. This was not a simulation of professional work; it was the work itself.

The pedagogical gamble was that generative AI could absorb the procedural burden that historically made such ambitious assignments impractical for novices. Authentic assessment, the idea that students should be evaluated on tasks resembling real professional practice, has struggled for decades with a built-in tension: authentic tasks demand competencies students have not yet developed, and the scaffolding needed to bridge that gap often dilutes the authenticity it is meant to support. Sidorkin’s argument is that a capable language model changes this calculus. A student who previously could not construct a conventional methods section or navigate disciplinary terminology can now obtain that support on demand, shifting the locus of difficulty away from routine production and toward decisions about evidence, interpretation, and methodological fit.

Crucially, the course did not treat AI as a threat to be policed. Students used a custom course-specific tool, the CHDE 111 Class Companion, a configured GPT that offered navigation, concept clarification, assignment protocols, and rubric-based draft review while explicitly instructed to support learning without providing completed assignments. They were also free to use ordinary ChatGPT or other major platforms without limitation, and the syllabus placed responsibility for the quality, veracity, and originality of the final product squarely on the student. For most assignments, students submitted complete logs of their AI conversations alongside their work, making part of the human-machine interaction visible for feedback and analysis.

To measure whether unrestricted AI access compressed student outputs, the study applied three rule-based indicators to the 33 final manuscripts. The Methods Specificity Index, a 0-to-6 scale scoring the presence of six methodological components such as a named qualitative approach, a concretely specified data source, sampling logic, analytic procedure, ethical safeguards, and a rationale connecting method to question, showed dramatic upper-bound compression. The median score was the maximum of 6, nearly 70 percent of manuscripts received the full score, and 97 percent scored either 5 or 6. Methodological specification, in other words, had become something AI scaffolding could reliably deliver.

The other two indicators told a different story. Claim-Evidence Coupling, the proportion of interpretive statements locally accompanied by specific evidentiary support such as a quotation, citation, or reference to the study data, ranged from 0.000 to 0.750 with a median of 0.333. Theory-Interpretation Linkage, the proportion of interpretive statements that explicitly invoked the manuscript’s own theoretical framework, ranged from 0.000 to 0.917 with a median of 0.444. Both remained substantially dispersed across the corpus. Students differed enormously in whether their interpretive claims were tethered to actual evidence and whether theory genuinely informed their analysis, dimensions that AI can assist with but cannot resolve, because warranting a claim depends on the actual data and argument of each individual project.

This differential pattern is the study’s central empirical finding. Compression appeared where structural scaffolding suffices; dispersion persisted where situated judgment is required. The theoretical framework behind the study, drawing on the five-dimensional authentic assessment model of Gulikers and colleagues, holds that when professionals routinely use AI, an assessment that categorically excludes it may actually resemble professional work less faithfully. Student contribution, in this view, is not independent text production but the direction, evaluation, integration, and revision of work produced within a human-AI system, a capacity the study terms extended executive cognition, paired with discerning thinking, the ability to judge AI output for substance and fit rather than equating fluency with quality.

Detailed comparison of four contrasting students, two from the top and two from the bottom of the course-points distribution, illuminated what those differences look like in practice. The stronger students orchestrated their AI use: they specified tasks precisely, supplied information the model could not infer, such as which social media discourse threads belonged in the analysis, repeatedly asked the Companion to audit sections for coherence, and pushed through multi-turn revision cycles until the conceptual fit was right. One student rejected a Companion-generated framework summary as misaligned with her research question and iterated across several turns until satisfied. The weaker students, by contrast, engaged in sparse, one-directional interactions, accepting template language and structural outlines without constraining them to the specifics of their actual studies. Their manuscripts could look competent at a glance, but theme statements were thin on evidence and theory was named rather than deployed.

The study is candid about its limits. It is a single-semester case study without a comparison group, so it cannot isolate AI orchestration from prior preparation, effort, or research aptitude. The three indicators are heuristic measures applied with the assistance of ChatGPT rather than validated instruments, and the instructor, course designer, tool designer, analyst, and author are all the same person, a concentration of roles that creates real confirmation-bias risk despite safeguards such as fixed rules and independent case selection. The process evidence also covers only a late slice of the semester, so it cannot show whether orchestration practices developed through instruction or simply differed among students from the start.

Even with those caveats, the implications are significant for anyone designing courses in the AI era. The study suggests that authentic assessment can remain viable and diagnostically useful when instructors explicitly distinguish between dimensions AI can scaffold reliably and dimensions where student judgment remains consequential, then align tasks, feedback, and rubrics accordingly. It also suggests that AI orchestration itself should become an instructional object, modeled and taught rather than assumed, and that when AI can generate prose quickly, the bottleneck shifts toward reading, evaluating, and revising it. Whether the pattern transfers across disciplines and institutions remains an open empirical question, but the Sacramento case demonstrates that giving every student a powerful AI assistant did not make them interchangeable. The tool was common; the judgment was not.

Subject of Research: Authentic assessment and student judgment in an AI-integrated undergraduate qualitative research methods course

Article Title: Authentic assessment in an AI-integrated qualitative research methods course

Article References: Sidorkin, A. M. (2026). Authentic assessment in an AI-integrated qualitative research methods course. Discover Education, 5(1), Article 1153. https://doi.org/10.1007/s44217-026-02273-4

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02273-4

Keywords: authentic assessment, generative AI, qualitative research methods, undergraduate education, evaluative judgment, human-AI collaboration, assessment design, rubric, extended executive cognition, pedagogy, case study, academic writing

The researchers frame appropriate technology as sitting at the intersection of three demands that are often in tension: economic viability, environmental sustainability, and social acceptability. A technology that is cheap but degrades soil, or one that is ecologically sound but culturally alien to its intended users, fails the test. This tripartite framework draws on the intellectual lineage of the movement, which traces back to E. F. Schumacher’s 1973 classic Small Is Beautiful and its argument that economics should be conducted as if people mattered. The study argues that this balance is not achieved by the technology itself but by the institutional environment surrounding it, which is where government enters the picture.

To examine how state support shapes outcomes, the authors analyze case studies from two very different settings: Southern China and the Morogoro Province of Tanzania. The comparative design is deliberate. China represents a state with deep administrative capacity and a long history of agricultural extension work, while Tanzania illustrates the challenges of a lower-income economy where government resources are thinner and infrastructure more limited. By holding the analytical framework constant across both cases, the study isolates which elements of government intervention matter most, and how those elements must be adapted to different stages of development.

The central finding is that successful appropriate technology initiatives depend on support operating at multiple levels simultaneously. Policy support establishes the legal and financial framework, signaling to researchers, firms, and farmers that the technology is a serious national priority. Pilot projects provide controlled environments in which new tools and techniques can be tested, refined, and demonstrated before wider rollout. Technical extension services then carry the technology to the field, translating scientific knowledge into practical guidance that farmers can apply on their own plots. Remove any one of these layers, the study suggests, and the whole structure becomes fragile.

Perhaps the most striking insight concerns skepticism. Farmers in both regions were initially reluctant to adopt unfamiliar technologies, and the authors argue that this reluctance is rational rather than backward-looking. A smallholder who stakes an entire season’s income on an unproven seed variety or irrigation method risks catastrophic loss if the technology fails. Overcoming this barrier required visible demonstrations, sustained trust-building between extension agents and farming communities, and careful adaptation of the technologies to local conditions. Trust, in other words, is not a soft afterthought but a hard prerequisite, built through repeated, verifiable successes rather than persuasion alone.

The Chinese cases illustrate how a mature extension infrastructure can accelerate this process. China’s system of science and technology backyards, in which researchers live and work alongside farmers, exemplifies the kind of sustained, place-based engagement that the study identifies as effective. Rather than delivering one-off training sessions, these arrangements embed technical expertise within the community, allowing problems to be diagnosed and solved in real time. The approach reflects a broader lesson from the agricultural economics literature: agricultural productivity growth is among the most reliable pathways out of rural poverty, but only when adoption is broad enough to lift incomes across whole communities rather than enriching a few early adopters.

The Tanzanian cases, by contrast, show both the promise and the limits of appropriate technology in a lower-capacity setting. Field trials of hybrid maize varieties in Morogoro Province, documented in earlier research cited by the authors, demonstrated that yields could be improved with varieties suited to local growing conditions. But translating trial results into widespread adoption requires the same layered support structure that China has built over decades: reliable seed distribution, financing mechanisms, demonstration plots, and extension agents who understand both the science and the social fabric of the villages they serve. Where these layers are thin, promising technologies stall at the pilot stage.

The study is candid about the movement’s troubled history. Critics have argued since the 1980s that appropriate technology was often long on idealism and short on market discipline, with the pointed observation that if a technology cannot be sold, it should not be promoted. Technologies that nobody was willing to pay for, the critique runs, were probably not appropriate after all. The authors respond to this critique not by abandoning the concept but by refining it: appropriateness must be evaluated dynamically, across the three dimensions of economic, environmental, and social performance, and it must be governed rather than assumed. A technology that is appropriate in one institutional context may fail in another, and the difference lies in how the surrounding system is designed.

This reframing has significant policy implications. For governments in developing countries, the study recommends sequencing interventions according to developmental stage. In early stages, when farmer skepticism is highest and infrastructure weakest, investment in demonstrations, pilot projects, and trust-building yields the greatest returns. As adoption spreads, the emphasis can shift toward strengthening supply chains, financing, and market linkages that allow the technology to become self-sustaining. In more advanced stages, the focus moves to continuous innovation and adaptation, ensuring that technologies evolve alongside changing environmental and economic conditions. The study also contributes to a growing body of evidence on the poverty-reduction effects of agricultural technology adoption, from improved cassava varieties in Nigeria to crop income gains in Uganda, suggesting that the returns to well-governed technology interventions are substantial.

The broader significance of the work lies in its treatment of technology as a governance problem rather than an engineering problem. As debates about artificial intelligence, biotechnology, and climate adaptation dominate headlines, the humble question of whether a smallholder farmer will adopt a new technique remains one of the most consequential in global development. Smallholder farms produce a substantial share of the world’s food, and the livelihoods of hundreds of millions of people depend on their productivity. Zang and Gai’s analysis suggests that the tools needed to improve those livelihoods often already exist; what is missing is the patient, layered institutional work of making them trusted, affordable, and locally fitting. In that sense, the study offers a quietly radical message: the future of poverty alleviation may depend less on inventing new technologies than on governing the ones we have.

Subject of Research: Government-supported appropriate technology adoption for smallholder poverty alleviation in China and Tanzania

Article Title: Governing appropriate technology: policy strategies for smallholder empowerment and poverty alleviation

Article References: Zang, L., & Gai, J. (2025). Governing appropriate technology: policy strategies for smallholder empowerment and poverty alleviation. Global Public Policy and Governance, 5(1), 46-62. https://doi.org/10.1007/s43508-025-00109-9

Image Credits: AI Generated

DOI: 10.1007/s43508-025-00109-9

Keywords: appropriate technology, smallholder farmers, poverty alleviation, agricultural extension, government policy, sustainable development, China, Tanzania, technology adoption, rural development, case study, public governance