Effects of instructive feedback on future learning

1993 ◽  
Vol 3 (3) ◽  
pp. 259-285 ◽  
Author(s):  
Ariane Holcombe ◽  
Mark Wolery ◽  
Margaret Gessler Werts ◽  
Patricia Hrenkevich
Keyword(s):  
Instructive Feedback ◽  
Future Learning

Themes, Diction, and Prosodic Systems in Yoruba Lullabies

2019 ◽  
Vol 12 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Olusanmi Babarinde ◽  
Elizabeth Babarinde
Keyword(s):  
Participant Observation ◽  
Cultural Beliefs ◽  
Survey Method ◽  
World Views ◽  
Scholarly Research ◽  
Long Term Consequences ◽  
Analyse Data ◽  
Descriptive Survey ◽  
Future Learning

Lullabies are essentially sung for their soothing nature but, as this article shows, they have other important functions. One of the most important of these is that lullabies may provide much-needed language stimulation with important long-term consequences for future learning. This paper begins the work of addressing the dearth of scholarly research on lullabies, especially in the Yoruba (Nigeria: Niger-Congo) culture. It looks at the range of themes, dictions, and prosody that are intertwined to reveal Yoruba beliefs and world-views about children, starting with their time in the womb. The study uses a descriptive survey method to analyse data collected through participant observation. It shows that Yoruba lullabies not only offer insights into Yoruba cultural beliefs but also depend greatly on figurative expression and prosodic systems. These rich literary qualities identify lullabies as the earliest sub-genre of children's poetry.

Promoting positive washforward through personalised test feedback and other benefits: Piloting a computer-based testing system

2020 ◽  
Vol 10 (1) ◽  
pp. 235-244
Author(s):  
Elena A. M. Gandini ◽  
Tania Horák
Keyword(s):  
Foreign Language ◽  
Testing System ◽  
Test Results ◽  
Test Feedback ◽  
Teachers And Students ◽  
Computer Based ◽  
Computer Based Testing ◽  
The University ◽  
Future Learning ◽  
Personalised Feedback

AbstractThis contribution reports on the developing and piloting of a computer-based version of the test of English as a foreign language produced by the University of Central Lancashire (UCLan), where it is currently used for the admission of international students and the subsequent evaluation of their language progress. Among other benefits, computer-based testing allows for better and individualised feedback to both teachers and students, and it can provide a more authentic test experience in light of the current digital shift that UK universities are undergoing. In particular, the qualitative improvement in the feedback available for test-takers and teachers was for us a crucial factor. Providing students with personalised feedback, that is, directly linked to their performance, has positive washforward, because it means we can guide their future learning, highlighting the areas they need to work on to improve their language skills and giving them suggestions on how to succeed in academia. Furthermore, explaining the meaning of test results in detail improves transparency and ultimately washback, as teachers can use the more accessible marking criteria, together with information on how their students performed, to review plans and schemes of work for subsequent courses.

scholarly journals Future Learning: Coaching im Jahr 2030

2021 ◽  
Vol 3 (2) ◽  
pp. 42-43
Author(s):  
Alexander Brungs
Keyword(s):  
Future Learning

Responses to music: Emotional signaling, and learning

2008 ◽  
Vol 31 (5) ◽  
pp. 580-581 ◽  
Author(s):  
Martin F. Gardiner
Keyword(s):  
Human Evolution ◽  
Neural Mechanisms ◽  
Target Article ◽  
Future Learning

AbstractIn the target article, Juslin & Västfjäll (J&V) contend that neural mechanisms not unique to music are critical to its capability to convey emotion. The work reviewed here provides a broader context for this proposal. Human abilities to signal emotion through sound could have been essential to human evolution, and may have contributed vital foundations for music. Future learning experiments are needed to further clarify engagement underlying musical and broader emotional signaling.

Scaffolding student engagement with written corrective feedback: Transforming feedback sessions into learning affordances

2021 ◽  
pp. 136216882110409
Author(s):  
Chi-Duc Nguyen
Keyword(s):  
Student Engagement ◽  
Language Learning ◽  
Error Correction ◽  
Corrective Feedback ◽  
Attentional Focus ◽  
Assessment Practice ◽  
Writing Conference ◽  
Teacher Student ◽  
Written Corrective Feedback ◽  
Future Learning

This study proposed a three-step writing conference in which foreign/second language (L2) students, under the guidance of their writing instructor, first fastened their attentional focus on a form-related error, analysed a collection of standard L2 samples to deduce the underlying knowledge, and then planned for their error correction as well as future learning of this knowledge. The ultimate goal of this formative assessment practice was to scaffold student engagement with written corrective feedback (WCF). Using a between-group experiment design, the present study compared the effects on the success rate of error correction and L2 uptake of the above writing conference ( n = 14) against those brought about by a typical Teacher–Student ( n = 12) and a typical Student–Student one ( n = 12). Research participants were 38 intermediate learners of English as a Foreign Language (EFL) recruited from three intact classes at a language-learning center in Vietnam. The suggested writing conference was indeed found to yield better error correction and L2 uptake than the other counterparts. A closer look at the students’ mental engagement with WCF revealed that such engagement was moderately correlated with their L2 uptake. These findings altogether suggest that student engagement with WCF should not be taken for granted or, in other words, this engagement should be contingently supported by the writing instructor in order to foster learning from WCF.

I want to learn more! Integrating technology acceptance and task–technology fit models for predicting behavioural and future learning intentions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alessandro Lo Presti ◽  
Assunta De Rosa ◽  
Enrico Viceconte
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Ease Of Use ◽  
Perceived Ease Of Use ◽  
Content Type ◽  
Moderated Mediation Model ◽  
Task Technology Fit ◽  
Acceptance Model ◽  
Training Opportunities ◽  
Future Learning

Purpose Constant and frequent technological changes within organizations call for further scholarly attention, as behavioural intentions need to be coupled also with future learning intentions to predict the present and prospective individual adaptations and performance. This study, grounded on the technology acceptance model, aims to examine the association between training opportunities and behavioural and future learning intentions also taking into account the role of task–technology fit as a moderator. Design/methodology/approach A survey was carried out within a single organization in the water processing sector on a sample of 200 workers who recently experienced a technological change through the adoption of System Application and Product in data processing. A moderated–mediation model was estimated through regression analyses with bootstrapping. Findings The results were consistent with study hypotheses. In particular, task–technology fit amplified the positive association between perceived ease of use and training opportunities as well as the indirect effect of this latter on both behavioural and future learning intentions through perceived ease of use and perceived usefulness. In sum, the hypothesized moderated–mediation model was confirmed. Originality/value Three novelty factors of this study can be stressed: it is among the few studies carried out on Italian workers in the realm of technology adoption, it expanded the technology acceptance model by including traditional behavioural intentions and future learning intentions as outcome variables and it integrated the task–technology fit perspective within the technology acceptance model.

Sign in / Sign up

Export Citation Format

Share Document