Conversations with Preschoolers: The Feeling State Content of Children's Narratives

This study examined the feeling state content of 3- and 4-year-olds' narratives. Four times throughout the school year, each child was paired with a familiar adult and provided an opportunity to talk with the adult about his/her day. Children's narratives were then coded for their feeling state content. Results revealed that children talk a great deal about affiliation, that sex differences emerge only in the context of interactive talk between adults and children, and that older children talk more about emotions than younger children when speaking spontaneously, but that these differences disappear when adults are able to provide “scaffolding” to the younger, less experienced, children.     

Influencing the Future Through Innovations in Environmental Engineering Education

Global scenarios for the next 30 years indicate increasing population, greater demand for higher standards of living, and more consumption, leading to increased air, water and land pollution; climatic change; and the depletion of and competition for natural resources. To avoid global catastrophes and conflicts, sustainable systems are required that integrate cultural and technological change. Engineers and technologists have a key role not only in developing sustainable technologies but also in promoting the cultural changes needed. High quality environmental education and training is essential if engineering professionals are to become pro-active rather than reactive, to influence the future. This paper describes examples of innovative educational and training systems, partnerships and networks with regional, national and international objectives.     

A method for sequencing instructional objectives which minimizes memory load

A Gagné-style learning hierarchy often permits a large number of alternate linear arrangements (sequences) of instructional objectives. An alternative is described here to traditional methods of choosing between sequences. Its premise is that, for every sequence, a value temed thememory load can be calculated which is theoretically related to the probability that students will fail to recall prerequisite objectives. A graph theoretic approach is taken in presenting an algorithm which generates a minimal memory load sequence from a learning tree, a restricted but frequently encountered type of learning hierarchy. In order to assess the effectiveness of the algorithm in generating low memory load sequences when given hierarchies which are not trees, it was applied to several published examples of learning hierarchies. The results indicated that the algorithm is effective as an heuristic, especially when combined with a hill-descending procedure which attempts to incrementally improve the generated sequence.