Climate change constitutes a major threat to agricultural production, food security, and natural resource management. Saudi Arabia is particularly susceptible to increasing temperatures and extreme climatic events, such as arid weather and drought. The purpose of this study is to assess farmers’ beliefs and concerns as regards climate change. Extensive interviews were conducted with 164 farmers in the Jazan region. Results revealed that 89.6% of the farmers believed that climate change is due to human activities and 93.3% believed that it is because of natural change. Seventy-five percent of the farmers were concerned about insects and 73% about the prevalence of weeds on their farms. Findings of cluster analysis revealed that farmers who are more likely to believe in climate change are more in agreement with the role of extension services in capacity building. Farmers’ beliefs about climate change were significantly influenced by membership of agricultural cooperatives, access to loans, use of extension services, age, farm size, and level of soil fertility. Access to loans was the only significant factor to explain the differences in farmers’ concerns. These results suggest the need for capacity-building activities targeted at improving farmers’ adaptability to manage climate variability.

The sustainability of global food production has been facing many threats, including climate change. The adaptation to such threats is both a challenge as well as an opportunity, especially for woman-operated farms in Pakistan. The challenge is how to devise measures and look for options to counter its impact, while the opportunity lies in developing new techniques, skills, and interventions leading to innovativeness. As women farmers are constrained regarding resources, cultural, societal, and personal reasons in Pakistan’s context, they particularly need innovative behavior and decision power to adapt to climate change. This study aims to measure the decisional empowerment and innovativeness of women farmers and their role in adopting different climate-smart agricultural (CSA) practices at the farm level. To this end, data from 384 farms where women were majorly involved are utilized in a multivariate probit model and propensity score matching to reveal various aspects of women’s role in adopting CSA practices. Results reveal that most women farmers lacked decisional power related to productive resources such as sale/purchase and renting of farmland, using farm machinery, and availing credit. Their decisional empowerment and innovativeness positively affected the adoption of CSA practices at the farm level. Females with more decisional power and innovativeness adopted more CSA practices than women with weaker decisional power and innovativeness. Therefore, the world can benefit greatly from giving more power to women in agriculture in terms of increased adoption of CSA practices, consequently improving food security and mitigating climate change. This outcome will assist in achieving the United Nation’s Sustainable Development Goals of gender equality (SDG5) and climate action (SDG 13).

Climate change is a serious threat to the sustainability of global agriculture and food supply that necessitates taking appropriate action for building resilient food production systems and preserving rural economies. In this regard, farmers’ beliefs and concerns about the effects of climate change on agriculture may influence their adoption of adaptation and mitigation practices to address this emerging issue. This work was undertaken to evaluate farmers’ level of concern about climate change in the Jazan province of Saudi Arabia. The study also explored the role of various socioeconomic indicators in shaping farmers’ concerns and highlights various capacity-building initiatives that can be applied at the community level for effective adaptation. Ordered logistic regression was used to study the relationship between farmers’ level of concern and their need for capacity-building initiatives to tackle climate change. Results indicated that insect infestation is the farmers’ top concern, followed by higher crop-diseases incidence and drought. Regression analysis revealed that farmers’ income is a major factor that reduces their concern for insect infestation and crop disease while increases concern for drought. Credit access and information availability have a mixed impact on the farmers’ concern level. Capacity-building initiatives deemed necessary included establishing frequent contacts with extension personnel, timely warnings on droughts and other natural hazards, the training of farmers and extension workers, easy credit facilities, improvement in rural infrastructure and creation of awareness to address specific concern stimulus.

We present our findings from the first shared task on Multi-task Learning in Dravidian Languages at the second Workshop on Speech and Language Technologies for Dravidian Languages. In this task, a sentence in any of three Dravidian Languages is required to be classified into two closely related tasks namely Sentiment Analyis (SA) and Offensive Language Identification (OLI). The task spans over three Dravidian Languages, namely, Kannada, Malayalam, and Tamil. It is one of the first shared tasks that focuses on Multi-task Learning for closely related tasks, especially for a very low-resourced language family such as the Dravidian language family. In total, 55 people signed up to participate in the task, and due to the intricate nature of the task, especially in its first iteration, 3 submissions have been received.

The world faced COVID-19, which was a threat to public health and disturbed the educational system and economic stability. Educational institutes were closed for a longer period, and students faced difficulty to complete their syllabus. The government adopted a policy of “suspending classes without stopping learning” to continue education activities. However, student satisfaction with online education is a growing concern. Satisfaction of students is an important indicator of academic quality. Therefore, this study attempts to investigate the influencing factors behind learning satisfaction using information from 335 students from various institutes in Pakistan. This research examined the impact of computer and internet knowledge, instructor and course material, and Learning Management Systems (LMS) on learning satisfaction. The path coefficients were obtained via Partial Least Square-Structural Equation Modeling (PLS-SEM). The LMS is a tool that facilitates the learning process with the provision of all types of educational material. The path coefficient was more in the case of LMS (0.489), which indicates its positive and significant role to attain learning satisfaction. The instructor and course material ordered second (0.261), which shows that the quality of an instructor and course material also plays a positive role to attain learning satisfaction. The computer and internet are essential ingredients of online education, showing a significant and positive path coefficient (0.123), implying that computer and internet knowledge could enhance learning satisfaction. The universities should develop their LMS to implement online education with quality course materials. It is also vital that the instructor should be up to date with modern learning techniques while ensuring internet connectivity, especially in rural areas. The government should provide an internet connection to students at discounted rates.