Selecting valuable information to remember: Age-related differences and similarities in self-regulated learning.

2013 ◽  
Vol 28 (1) ◽  
pp. 232-242 ◽  
Author(s):  
Alan D. Castel ◽  
Kou Murayama ◽  
Michael C. Friedman ◽  
Shannon McGillivray ◽  
Ian Link
2019 ◽  
Vol 63 (1) ◽  
pp. 74-97 ◽  
Author(s):  
Susan-Marie Harding ◽  
Narelle English ◽  
Nives Nibali ◽  
Patrick Griffin ◽  
Lorraine Graham ◽  
...  

Students who can regulate their own learning are proposed to gain the most out of education, yet research into the impact of self-regulated learning skills on performance shows mixed results. This study supports the link between self-regulated learning and performance, while providing evidence of grade- or age-related differences. Australian students from Grades 5 to 8 completed mathematics or reading comprehension assessments and self-regulated learning questionnaires, with each response ranked on a hierarchy of quality. All assessments were psychometrically analysed and validated. In each cohort and overall, higher performing students reported higher levels of self-regulated learning. Still, age-related differences outweighed performance differences, resulting in significantly lower reported usage of self-regulated learning skills in Grade 7 students compared to those in Grades 5, 6 and 8. These findings suggest that either age or school organisational differences mediate students’ self-regulated learning, counteracting ability-related associations.


2022 ◽  
Vol 3 ◽  
Author(s):  
Anna Schlomann ◽  
Christiane Even ◽  
Torsten Hammann

Learning to use information and communication technologies (ICT) may be more difficult for older people due to decreases in fluid intelligence, generational effects, and other age-related effects. Especially older people with intellectual disabilities (ID) are at a high risk of digital exclusion. To enable all older adults to use ICT, individualized technology training may be provided. However, little is known about the ICT learning preferences among older people with ID. Based on semi-structured interviews with older adults (n = 7, mean age = 76.6 years) and older adults with ID (n = 14, mean age = 62.4 years), this paper analyzes learning strategies, preferences, and learning settings. The results from content analysis show that guided learning with personal explanations in a one-to-one setting is the most preferred learning format in both groups of older adults. While many older adults without ID additionally favor self-regulated learning (i.e., learning with manuals or videos), older adults with ID mostly rely on guided learning with personal assistance. The differences can be explained by different abilities (e.g., reading skills) and social networks (e.g., living situation, having children). Not all older adults have a family or an institutional support network to help them learn ICT and community organizations may provide additional support. Researchers and practitioners should be aware of the diverse knowledge backgrounds and competencies in the group of older adults. ICT training in old age should be ideally composed in a modular way embedding self-regulated learning formats into guided learning modules.


2018 ◽  
Vol 34 (3) ◽  
pp. 193-205 ◽  
Author(s):  
Julia Steinbach ◽  
Heidrun Stoeger

Abstract. We describe the development and validation of an instrument for measuring the affective component of primary school teachers’ attitudes towards self-regulated learning. The questionnaire assesses the affective component towards those cognitive and metacognitive strategies that are especially effective in primary school. In a first study (n = 230), the factor structure was verified via an exploratory factor analysis. A confirmatory factor analysis with data from a second study (n = 400) indicated that the theoretical factor structure is appropriate. A comparison with four alternative models identified the theoretically derived factor structure as the most appropriate. Concurrent validity was demonstrated by correlations with a scale that measures the degree to which teachers create learning environments that enable students to self-regulate their learning. Retrospective validity was demonstrated by correlations with a scale that measures teachers’ experiences with self-regulated learning. In a third study (n = 47), the scale’s concurrent validity was tested with scales measuring teachers’ evaluation of the desirability of different aspects of self-regulated learning in class. Additionally, predictive validity was demonstrated via a binary logistic regression, with teachers attitudes as predictor on their registration for a workshop on self-regulated learning and their willingness to implement a seven-week training program on self-regulated learning.


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