Self-perception of emotional development in individuals attending university programmes for seniors: training needs and answers

In older adults, emotional competencies become the most important reason to preserve quality of life. In this study we focused on Emotional Intelligence in a group of older adults. by means of examining the relationship between perceived emotional competencies and sociodemographic variables. A total of 255 older participants (72.2% women), mean age?=?64.59 years old (SD?=?5.82, range?=?52–83 years old), who attended the University of the Experience in Salamanca (Spain), were evaluated. Information on sociodemographic data, perceived health and motivation to take part in university programmes, and perceived emotional competence was collected using self-reported questionnaires. Results show significant differences, mainly in relation with sex and perceived health in various areas of emotional competence. These results open the way to design and implement quality intervention programmes that enhance social-emotional skills and personal and social well-being to improve quality of life of older people.     

Increasing the effectiveness of learning how to teach in preservice education

Interchange - In the context of re-examining teaching practice as an integral part of teacher education, two hypotheses were tested by a year-long experiment in preservice education of elementary...     

Wentzel,Kathryn R & Brophy,Jere E (2014) Motivating students to learn Routledge (New York & London) isbn 978‐0‐415‐89352‐7 301 pp £39.99 http://www.routledge.com/books/details/9780415893527/

The authors of Motivating students to learn offer teachers evidence‐based classroom strategies to motivate their students. This fourth edition draws comprehensively on current psychological and educational research on student motivation and extrapolates this to implications for teaching practice in the classroom. This book's aim is primarily school teachers but it may also be of interest to people in further and higher education. If you think this book's content could be relevant, I suggest you borrow a copy to decide whether it's worth buying. Sara Hammer     

Learning theories for artificial intelligence promoting learning processes

This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal learning mechanism that explains how learning occurs and works across micro, meso and macro levels. The model also explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels. Fourteen roles for AI in education are proposed, aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity. Implications for research and practice, evaluation criteria and a discussion of limitations are included. Armed with the proposed model, AI developers can focus their work with learning designers, researchers and practitioners to leverage the proposed roles to improve individual learning, team performance and building knowledge communities.

Practitioner notes

What is already known about this topic

• Numerous learning theories exist with significant cross-over of concepts, duplication and redundancy in terms and structure that offer partial explanations of learning.
• Frameworks concerning learning have been offered from several disciplines such as psychology, biology and computer science but have rarely been integrated or unified.
• Rethinking learning theory for the age of artificial intelligence (AI) is needed to incorporate computational resources and capabilities into both theory and educational practices.

What this paper adds

• A three-level theory (ie, micro, meso and macro) of learning that synthesizes and unifies existing theories is proposed to enhance computational modelling and further develop the roles of AI in education.
• A causal model of learning is defined, drawing from developmental psychology, computational biology, instructional design, cognitive science and sociocultural theory, which explains how learning occurs and works across the levels.
• The model explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels.
• Fourteen roles for AI in education are aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity.

Implications for practice and policy

• Researchers may benefit from referring to the new theory to situate their work as part of a larger context of the evolution and complexity of individual and organizational learning and learning systems.
• Mechanisms newly discovered and explained by future researchers may be better understood as contributions to a common framework unifying the scientific understanding of learning theory.

     

Three recommended inclusive language guidelines for scholarly publishing: Words matter

• Inclusive language will make scholarly publishing more accurate and more respectful, and it has the potential to help authors reach a wider audience.
• JAMA and the JAMA Network journals, the American Chemical Society and the Coalition for Diversity and Inclusion in Scholarly Communications have free guides on inclusive language, formatting and images.
• The guides provide principles and rationale, as well as examples of preferred language, in order to equip people with knowledge to choose the most inclusive words even as terminology preferences change.