Topic
Domain-specific learning
About: Domain-specific learning is a research topic. Over the lifetime, 22 publications have been published within this topic receiving 170 citations.
Papers
TL;DR: In this article, the authors compared the effects of support for peer feedback, peer feedforward and their combination on students' peer learning processes, argumentative essay quality and domain-specific learning.
Abstract: This study compared the effects of support for peer feedback, peer feedforward and their combination on students’ peer learning processes, argumentative essay quality and domain-specific learning. Participants were 86 BSc students who were randomly divided over 43 dyads. These dyads, in a two-factorial experimental design, were assigned to four conditions including: peer feedback (n = 22), peer feedforward (n = 22), mixed (n = 20) and control group (n = 22) conditions. An online peer feedback environment named EduTech was designed which allowed us to implement various types of support in the form of question prompts. In this online environment, students were asked to write an argumentative essay on a controversial topic, to engage in peer learning processes and to revise their essay. Overall, the results showed that students in the three experimental conditions (peer feedback, peer feedforward and their combination) benefited more than students in the control group condition (without any support) in term of peer learning processes, argumentative essay quality and domain-specific learning. However, there was no significant difference among the three experimental conditions. This implies that peer feedforward can be as important as peer feedback in collaborative learning environments which is often neglected both in theory and practice. Practitioner Notes What is already known about this topic? Writing argumentative essays is a common practice for higher education students in various disciplines which deal with controversial issues. Writing argumentative essay requires solid argumentation strategies which makes it a challenging task for higher education students. Additional instructional support is needed to help students write high-quality argumentative essays. What this paper adds? Peer learning is a promising instructional strategy for improving students’ argumentative essay writing and learning. Online support in the form of question prompts to guide students during peer learning can improve their argumentative essay writing and learning. Next to the peer feedback, peer feedforward is also a promising instructional approach to support students’ argumentative essay writing and learning. Implications for practice and/or policy Given the positive effects of peer learning processes, the use of peer feedback and peer feedforward should be given more attention by teachers to support students write high-quality argumentative essays for controversial issues. Teachers and educational designers should not only provide opportunities for students to engage in peer feedback processes (how I am doing?) but also in peer feedforward processes (where to next?).
107 citations
TL;DR: In this article, case studies of six domains (acting, reading, filmmaking, spelling, math, and preaching) describe how the passion developed using the voices of children and parents.
Abstract: Passion for learning (PFL) in children is a phenomenon that is little understood. The experience of PFL was studied with phenomenological and qualitative modes of inquiry. Case studies of six domains (acting, reading, filmmaking, spelling, math, and preaching) describe how the passion developed using the voices of children and parents. Their stories support variations in development across domains. The study demonstrates a fertile field for future research into domain-specific learning and advanced development.
25 citations
25 Sep 2009
TL;DR: The learner centered Adaptive E-learning Framework aims to provide a complete environment of online learning to address the ever increasing need and challenges associated with improving the state of web-based education.
Abstract: To address the ever increasing need and challenges associated with improving the state of web-based education, a synergistic view of E-Learning and intelligent and adaptive tutoring is adapted which is the basic essence of the learner centered Adaptive E-learning Framework presented in this paper. This framework aims to provide a complete environment of online learning. The conceptual architecture of the framework presented in this paper is centered around the following core features: (1) Domain Specific Learning Services (2) Student Capability Analysis (3) Adaptive Lecture Authoring Tool and Notification Manager (4) Intelligent Assessment Engine (5) User Friendly E-Learning Portal. Altogether, this framework is truly aimed to be an integrated platform consistent with the emerging needs of E-learning and Distance Education.
18 citations
TL;DR: It is found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences, and knowledge acquired in implicit learning is in some respects domain-specific and strongly linked to particular features of the stimulus domain.
Abstract: Artificial grammar learning depends on acquisition of abstract structural representations rather than domain-specific representational constraints, or so many studies tell us. Using an artificial grammar task, we compared learning performance in two stimulus domains in which respondents have differing tacit prior knowledge. We found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences. We also found transfer effects within the musical and letter name tasks, but not across the domains. We conclude that knowledge acquired in implicit learning depends not only on abstract features of structured stimuli, but that the learning of regularities is in some respects domain-specific and strongly linked to particular features of the stimulus domain.
15 citations
TL;DR: It is suggested that delineating learning into domain general and domain specific may be overly simplistic and the need to instead focus on individual variation in learning ability, which ultimately, is likely to play a key role in fitness.
Abstract: A key question in cognition is whether animals that are proficient in a specific cognitive domain (domain specific hypothesis), such as spatial learning, are also proficient in other domains (domain general hypothesis) or whether there is a trade-off. Studies testing among these hypotheses are biased towards mammals and birds. To understand constraints on the evolution of cognition more generally, we need broader taxonomic and phylogenetic coverage. We used Australian eastern water skinks (Eulamprus quoyii) with known spatial learning ability in three additional tasks: an instrumental and two discrimination tasks. Under domain specific learning we predicted that lizards that were good at spatial learning would perform less well in the discrimination tasks. Conversely, we predicted that lizards that did not meet our criterion for spatial learning would likewise perform better in discrimination tasks. Lizards with domain general learning should perform approximately equally well (or poorly) in these tasks. Lizards classified as spatial learners performed no differently to non-spatial learners in both the instrumental and discrimination learning tasks. Nevertheless, lizards were proficient in all tasks. Our results reveal two patterns: domain general learning in spatial learners and domain specific learning in non-spatial learners. We suggest that delineating learning into domain general and domain specific may be overly simplistic and we need to instead focus on individual variation in learning ability, which ultimately, is likely to play a key role in fitness. These results, in combination with previously published work on this species, suggests that this species has behavioral flexibility because they are competent across multiple cognitive domains and are capable of reversal learning.
14 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 3 |
| 2020 | 1 |
| 2018 | 2 |
| 2017 | 2 |
| 2014 | 1 |
| 2013 | 2 |