Graduate students often experience difficulties in learning statistics, particularly those who have limited mathematical backgrounds. In recent years, Learning Management Systems (LMS) and Problem-Based Learning (PBL) have been widely adopted to support instruction, yet little research has explored how these tools relate to learning outcomes using mixed methods design. Limited studies have employed machine learning methods such as clustering analysis in Learning Analytics (LA) to explore different behavior of clusters based on students log data. This study followed an explanatory sequential mixed methods design to examine student engagement patterns on Canvas and learning outcomes of students in a graduate-level statistics course. LMS log data and surveys were collected from 31 students, followed by interviews with 19 participants. K-means clustering revealed two groups: a high-performing group with lower LMS engagement and a low-performing group with higher LMS engagement. Six themes emerged from a thematic analysis of interview transcripts: behavioral differences in engagement, the role of assessment, emotional struggle, self-efficacy, knowledge or skill gain, and structured instructional support. Results indicated that low-performing students engaged more frequently and benefited from structured guidance and repeated exposure. High-performing students showed more proactive and consistent engagement habits. These findings highlight the importance of intentional course design that combines PBL with LMS features to support diverse learners.

In Haor areas of Bangladesh agricultural activities are limited to four - five months of a year due to water logged condition and boro rice is the prominent crop grown within this short time span in dry season. But farmers often had to face almost total crop failure due to recurrent flash flood events. This paper attempts to evaluate Haor farmers’ adaptation through adopting strategies in securing boro rice from flash flood damage at pre-mature and mature stages. To reach this objective, a pre-tested structured questionnaire was used to collect data from randomly selected 115 Haor farmers from February to May, 2020 while Focus Group Discussion (FGDs) and Key Informant Interviews (KIIs) were also done as necessary during the research work. Results revealed that cultivation of short duration boro rice variety ranked top followed by practicing varietal diversification and early harvesting of rice (at 80% maturity) as the most significant adaptive strategies in securing boro rice. Obtained results also highlighted the possibilities of attaining desirable resilience through change in the adaptation behavior of Haor farmers’ if the identified farming practices are widely promoted and adopted. Hence, any development plans for Haor area should integrate local knowledge with modern strategies thus resulting a location specific sustainable flash flood adaptation policy.

Water security is a multidimensional concept, but its meaning and application remain fragmented across research, policy, management, and public discourse. Because individuals, families, and communities are integral to socio-physical water systems, understanding their perceptions is important for sustainable and equitable water resource management. This scoping review synthesizes empirical research on perceptions of water security in the United States. Following PRISMA-ScR guidance, six databases were searched for publications from January 2010 to June 2025, yielding 10,711 records. After duplicate removal, title and abstract screening, and full-text review using predefined eligibility criteria, 167 empirical studies were included and coded using a shared codebook; intercoder reliability ranged from moderate to high. Research was geographically and socially uneven, with greater attention to western and southern states and to the general public, while low-income communities, Indigenous populations, rural minorities, producers, and officials were underrepresented. Across contexts, perceptions were associated with trust, lived experience, risk perception, knowledge, values, affordability, and policy preferences. The review identifies a conceptually multidimensional but analytically fragmented literature and proposes the Comprehensive Water Security Framework (CWSF), a three-domain architecture intended to support more comprehensive, comparative, and context-sensitive water-security research and assessment.

In response to the growing demand for data analytics competencies in Food, Agriculture, Natural Resources, and Human (FANH) Sciences, this study investigated how linguistic and demographic differences among learners can inform differentiated curriculum design. The objective was to identify distinct learner subgroups and explore how their expressed needs, tool preferences, and curricular priorities vary, thereby guiding the development of inclusive and responsive data analytics programs. Using a mixed-methods approach, the research team surveyed 535 alumni from a land-grant university, collecting both quantitative and qualitative data. Clustering analysis revealed two distinct groups: younger professionals emphasizing technical proficiency (e.g., coding, visualization, tool fluency), and older professionals prioritizing strategic competencies (e.g., leadership, communication, conceptual reasoning). Text mining of open-ended responses further highlighted divergent word usage patterns across curriculum dimensions, such as background tools, core topics, and supplemental skills, which validated the cluster distinctions. Key findings show that Group 1 (i.e., younger respondents with less work experience) favored hands-on, tool-centric learning, while Group 0 (i.e., older respondents with less education but with more experience) emphasized integrative applications and strategic thinking. These insights suggest that a one-size-fits-all curriculum is insufficient in curriculum design and development. Instead, differentiated learning pathways such as technical labs for early-career learners and strategic modules for experienced professionals are essential to accommodate learners’ needs. Communication skills emerged as a critical bridge across groups, underscoring the need to embed interpretive and collaborative competencies alongside technical training. This study demonstrates the value of combining linguistic analysis with demographic clustering to inform curriculum development. By aligning educational offerings with learner profiles and industry expectations, FANH science programs can better prepare graduates for diverse roles in data-driven agricultural and environmental science sectors.