Affective Computing to Enhance E-Learning in Segregated Societies

According to UN Women, to build stronger economies, it is essential to empower women to participate fully in economic life across all sectors. Increasing women and girls’ education enhances their chances to participate in the labor market. In certain cultures, like in Saudi Arabia, women contribution to the public economy growth is very limited. According to the World Bank, less than 20 percent of the female population participate in the labor force. This low participation rate has many reasons. One of them, is the educational level and educational quality for females. Although Saudi Arabia has about thirty three universities, opportunities are still limited for women because of the restrictions of access put upon them. A mixture of local norms, traditions, social beliefs, and principles preventing women from receiving full benefits from the educational system. Gender segregation is one of the challenges that limits the women access for education. It causes a problem due to the shortage of female faculty throughout the country. To overcome this problem, male faculty are allowed to teach female students under certain regulations and following a certain method of education delivery and interaction. However, most of these methods lack face-to-face communication between the teacher and students, which lowers the interactivity level and, accordingly, the students’ engagement, and increases the need for other alternatives. The e-learning model is one of high benefit for female students in such societies. Recognizing the students’ engagement is not straightforward in the e-learning model. To measure the level of engagement, the learner’s mood or emotions should be taken into consideration to help understanding and judging the level of engagement. This paper is to investigate the relationship between emotions and engagement in the e-learning environment, and how recognizing the learner’s emotions and change the content delivery accordingly can affect the efficiency of the e-learning process. The proposed experiment alluded to herein should help to find ways to increase the engagement of the learners, hence, enhance the efficiency of the learning process and the quality of learning, which will increase the chances and opportunities for women in such societies to participate more effectively in the labor market.

A case-control study of the health and wellbeing benefits of allotment gardening

Background - Allotments in the UK are popular and waiting lists long. There is, however, little evidence on the health benefits of allotment gardening. The aims of this study were to determine the impacts of a session of allotment gardening on self-esteem and mood and to compare the mental well-being of allotment gardeners with non-gardeners. Methods - Self-esteem, mood and general health were measured in 136 allotment gardeners pre- and post- an allotment session, and 133 non-gardener controls. Allotment gardeners also detailed the time spent on their allotment in the current session and previous 7 days, and their length of tenure. Results - Paired t-tests revealed a significant improvement in self-esteem (P < 0.05) and mood (P < 0.001) as a result of one allotment session. Linear regression revealed that neither the time spent on the allotment in the current session, the previous 7 days or the length of tenure affected the impacts on self-esteem and mood (P > 0.05). One-way ANCOVA revealed that allotment gardeners had a significantly better self-esteem, total mood disturbance and general health (P < 0.001), experiencing less depression and fatigue and more vigour (P < 0.0083). Conclusions - Allotment gardening can play a key role in promoting mental well-being and could be used as a preventive health measure