Universidade Metodista Unida de Moçambique [UMUM]

Partindo dos princípios que norteiam a UMUM, não esquecendo os pontos de referência da evolução transdisciplinar da educação – partir da/para a realidade – e tendo em mente que a estrutura student oriented sustenta a organização dos cursos, problematizamos a opção pela oferta, no 1º ano da licenciatura, de um conjunto de quatro disciplinas curriculares transversais a todos os cursos. Cientes de que a educação implica a vivência da interculturalidade e a inclusão social, o alvo é identificar o papel que a língua desempenha na descoberta do ‘eu’, na sua aceitação e consolidação, para que seja viável comunicar, agir e (con)viver em sociedade; na vivência pacífica do ‘eu’ com o ‘outro’; na construção colaborativa dos saberes e dos saberes fazeres. Daí decorre que as disciplinas curriculares transversais escolhidas, para induzir e potenciar uma educação de qualidade, tenham sido o Português, enquanto língua oficial, o Inglês, enquanto língua franca, as Tecnologias da Informação e Comunicação, como mediadoras da comunicação, promotoras de redes e de comunidades de aprendizagem para a construção do conhecimento e, ainda, Diálogos, Paz e Desenvolvimento, propiciando uma emergência equilibrada do sujeito per se, na sua relação com o ‘outro’ e com o mundo – saber ser e saber conviver. Questionamos a metodologia a utilizar nestas disciplinas curriculares, respeitando as suas especificidades, sustentando as áreas científicas contempladas em cada curso, numa dinâmica inter/transdisciplinar, implicando os estudantes na realidade e na complexidade do conhecimento e, em complementaridade, desafiando os docentes para o trabalho colaborativo.

Learning management systems in higher education

The use of Laptops and the Internet has produced the technological conditions for instructors and students can take advantage from the diversity of online information, communication, collaboration and sharing with others. The integration of Internet services in the teaching practices can be responsible for thematic, social and digital improvement for the agents involved. There are many benefits when we use a Learning Management Systems (LMS) such as Moodle, to support the lectures in higher education. We also will consider its implications for student support and online interaction, leading educational agents to a collaborating of different learning environments, where they can combine face-to-face instruction with computer-mediated instruction, blended-learning, and increases the possibilities for better quality and quantity of human communication in a learning background. In general components of learning management systems contain synchronous and asynchronous communication tools, management features, and assessment utilities. These assessment utilities allow lecturers to systematize basic assessment tasks. Assessments can be straightaway delivered to the student, and upon conclusion, immediately returned with grades and detailed feedback. Therefore learning management systems can also be used for assessment purposes in Higher Education.

Quality of Life Predictors and Normative Data

This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data

Quality of life predictors and normative data

Purpose: Identify predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population Methods: A cross-sectional correlational study was undertaken with two hundred and fifty-five (N=255) individuals from Portuguese general population (mean age 43yrs, range 25-84yrs; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument (WHOQOL-Bref) and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale (CES-D). Demographic information was also collected. Results: Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44% of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25% of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. Conclusions: The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL