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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?).

Most conceptions of giftedness have been based on intellectual and academic potential or aptitudes for high-level performance in a valued human endeavor. Individual characteristics have been used as markers for acknowledging advanced development at each stage of development. Moreover, these conceptions have driven our responses to advanced development in schools, in the work world, and in the larger society. As a society in general, we have chosen to ignore positive individual differences in favor of focusing on individual pathologies. Yet, some pockets of our society have always acknowledged the need for talent development through selective admission to mentorships and tutorials, advanced education, and work settings including the military, sports, and political spheres.

Mathematics difficulties (MD) are widespread. Higher mathematics achievement is associated with college success and greater job opportunities. In this chapter, we address the intersection between cognitive research on the science of learning and the education of students with MD. First, a conceptual framework for mathematics learning is provided, including consideration of individual differences in domain general and domain specific learning processes. Next, learning principles that promote successful learning in mathematics are described, along with examples of how the principles can be translated into educational practice for students with MD. We argue that in addition to providing developmentally appropriate instruction in content knowledge, such as whole number and fraction knowledge, application of more general learning principles validated by research will lead to deeper and more durable learning for struggling students. These learning principles include studying and comparing correct as well as incorrect worked out problem-solutions; using integrated visual and verbal models to reduce splitting attention; interleaving or varying practice with problems of different types; providing frequent cumulative practice or review that is spaced out over time; connecting and integrating concrete and symbolic representations; presenting arithmetic problems in different formats; using physical movements and gestures to promote learning; and incorporating activities with number lines to increase learning of whole numbers and fractions.

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.

A deep neural network, while avoiding its complex process of feature selection, requires sufficient training samples to learn those connection weights of adjacent layers. However, in many real applications, not enough training samples are available in all cases. This paper suggests a universal-to-domain-specific learning method based on recurrent neural network for cross-domain sentiment classifi- cation and activity recognition. In the situation of having only a small amount of training samples that is in available, the structure of its network model can be adjusted flexibly according to the needs of a target domain classification or recognition. Where there are two points of our concern as follows: 1) the fine-tune and regular constraints can increase its training efficiency by updating in a small local area, namely, sharing these parameters between input and hidden layers with a target domain and 2) then, a linear output network moves on its implementing amelioration from subtlety as an exploration or exploitation in order to mitigate the phenomenon of over-fitting. Aiming at an actual situation, this domain-specific learning model with a slide window of instances and features is designed and implemented for a good long-short term memory. Finally, the two strategies are applied into IMDB reviews, Amazon product reviews, and human activities recognition collected by the built-in gyroscope sensors data, and the experimental results verify their validity.

This article is a part of a research project aimed to find out how different background variables are related to learning outcomes in school subject Sloyd as found in the national evaluation of the Finnish National Board of Education. Results from this larger research project were previously published in this journal, where pupils’ readiness for Self-Regulated Learning were reported. Since then, pupils’ experiences of classroom techniques, attitudes towards the subject, leisure time interests and learning within the two domains of the subject (Technical Domain and Textile Domain, as the subject is usually divided in Finland) have been studied and results have been published in different journals. In this article, a new Structural Equation Model concludes the previous results. The new model highlights two paths of how the use of different learning orientations can predict successful learning outcomes. These paths can be followed using two pedagogical models: the Exploratory Production Approach and the Domain Specific Approach. Experiencing Learner-Centred Learning predicts positive attitudes and success in Exploratory Production activities. Experiencing Collaborative Learning predicts success in domain specific learning outcomes. Success in Exploratory Production predicts successful learning outcomes in both domains. The conclusion is that regulatory knowledge, “why”, is related to production activities and it is processed prior to domain specific knowledge, “what” and “how”. To develop the subject and pedagogy for schools and teacher training, it is not important to follow an approach defined by the domains (technical or textile). It is more important to teach pupils how to manage in the modern technological world and to understand why they need to be able to improve their life-world through Exploratory Production activities.

Dynamic assessment (DA) involves providing instruction and indexing students' responsiveness as a measure of learning potential. The purpose of this study was twofold: (a) to test whether a decoding DA measures early reading learning potential that is distinct from what can be assessed from static intelligence and decoding assessments; and (b) to examine the additive value of a decoding DA for explaining word reading and arithmetic performance beyond that which can be explained with static measures. First grade students (N = 112) were assessed on DA and measures of reading- and math-related predictors as well as domain-general learning indicators. Confirmatory factor analyses supported that DA measures early reading learning potential different from general intelligence and actual level of decoding. Structural equation models showed that DA was necessary in explaining only concurrent decoding skill beyond domain general learning measures and predictors of reading, suggesting that DA measures domain specific learning potential.

[EN] At the current rate of technological development, in a world where enormous amount of data are constantly created and in which the Internet is used as the primary means for information exchange, there exists a need for tools that help processing, analyzing and using that information. However, while the growth of information poses many opportunities for social and scientific advance, it has also highlighted the difficulties of extracting meaningful patterns from massive data. Ontologies have been claimed to play a major role in the processing of large-scale data, as they serve as universal models of knowledge representation, and are being studied as possible solutions to this. This paper presents a method for the automatic expansion of ontologies based on corpus and terminological data exploitation. The proposed ¿ontology enrichment method¿ (OEM) consists of a sequence of tasks aimed at classifying an input keyword automatically under its corresponding node within a target ontology. Results prove that the method can be successfully applied for the automatic classification of specialized units into a reference ontology., Financial support for this research has been provided by the DGI, Spanish Ministry of Education and Science, grant FFI2011-29798-C0201.

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.

Learning physics is a difficult endeavour since our everyday experiences frequently result in naive theories which do not or do only partly correspond to scientific concepts. If instruction does not take these well-known conceptions as a starting point for learning processes and neglects typical learning difficulties, it is likely to be non-effective. This holds true for all areas of physics, also for introductory optics. This article reports the development and evaluation of research based teaching materials. These teaching materials take domain specific learning problems known from research into account. In addition, they are based on an atypical content structure which was developed based on Design Based Research. The current version of the optics course was evaluated in year 8 physics classes. The comparison of Austrian students’ achievement after conventional instruction in optics in year 8 (N = 16 classes) and students instructed with our optics course (N = 5 classes) will be reported.

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.

Objectives: To determine causes for underachievement using a multi dimensional assessment battery. Meth- od: The students who consented to participate in study were segregated as achievers and underachievers based on scores in University's assessment and both the groups were subjected to a battery of assessments which included Memletics learn- ing styles inventory, Depression anxiety stress scale (DASS), and Study habits questionnaire to determine learning styles, emotional factors and study habits respectively. Results: A total of 103 out of 150 students participated in the study. Among these 50 were (48.5 %) classified as underachievers. The comparison of learning styles between achieving and underachieving group shows that the pre- dominant learning style in the achieving group is multimodal learning style (32 %) while that among the underachievers is single modality learning style, (40 % had visual learning style). Though the difference is not significant, low frequency of multi modal learn- ers in the underachieving group emphasizes the importance of including domain specific learning strategies. The achieving group scored lower than underachieving group on depression (6.42+5.25 and 8.19+5.87 respectively), anxiety (6.78+5.16 and 7.83+5.22) and stress (7.19+5.47 and 8.06+5.28) with female gender being more vulnerable. Assessment of study habits showed that items like being up to date on assignments and participation in group discussions positively correlated with achievement. Conclusion: The need for understanding the learning styles and adopting a multimodal teaching strategies to match these styles and the necessity for a professional team to help the students to handle emotions were implicated from this study.

Scripts for computer-supported collaborative learning (CSCL scripts) usually provide just-in-time support for learners to engage in a meaningful collaborative learning process that eventually leads to domain-specific learning. In contrast, CSCL scripts are often criticized to hamper the naturally emerging processes in collaborative learning, and research about the effectiveness of CSCL scripts has shown divergent results. Therefore, this paper reports a meta-analytical integration of k = 33 effects on domain-specific learning that have been reported in recent research about CSCL scripts. Results show that on average CSCL scripts actually support the engagement in meaningful collaborative learning processes leading to a positive effect on domain-specific learning outcomes compared to unstructured collaborative learning (d = 0.20, p = 0.02). Further analyses show that the effectiveness of CSCL scripts can be increased by combining them with domain-specific content scaffolds and by designing them in a way that might induce transactivity (i.e. activities by which learners refer to their learning partners' contributions). Limitations and implications of this meta-analysis are discussed.

Successful integration of traditional learning objectives with elements of entertainment becomes the goal for the design and application of video games used for educational purposes. Oftentimes assumptions are made that students who are not gamers can play video games and reap the pedagogical benefits of gameplay without experiencing a learning curve relative to understanding game objectives. We argue that inexperienced players encounter two different trajectories of learning: the cognitive process associated with understanding how to play the game and the cognitive processes embedded in gameplay activities that correspond to domain specific learning goals. These dissimilar trajectories of learning create competing goals for the player who portrays dual roles of student and novice gamer. We examine this dilemma in the context of second language students who play a Massively Multiplayer Online Role Playing Games for the purpose of improving their English proficiency skills. We utilize statistical analysis to evaluate English as Second Language (ESL) students' ability to acquire second language vocabulary. Results indicate positive learning outcomes for vocabulary acquisition of ESL students who participate in collaborative gameplay with Native English Speakers, emphasizing the role of social interactions in second language acquisition. However, visual analysis of game logs measures the learning trajectory associated with completing game tasks and reveals that ESL students who play EQ2 independently achieve increasing levels of virtual character progression in less time than their peers.

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.

As far as acquisition of language is concerned, it seems clear that reinforcement, casual observation, and natural inquisitiveness (coupled with a strong tendency to imitate) are important factors, as is the remarkable capacity of the child to generalize, hypothesize, and “process information” in a variety of very special and apparently highly complex ways which we cannot yet describe or begin to understand, and which may be largely innate, or may develop through some sort of learning or through maturation of the nervous system. The manner in which such factors operate and interact in language acquisition is completely unknown. It is clear that what is necessary in such a case is research, not dogmatic and perfectly arbitrary claims, based on analogies to that small part of the experimental literature in which one happens to be interested. Noam Chomsky (1959), A review of Skinner’s “Verbal Behavior” Language is arguably the most complex system acquired by humans. This fact, combined with the tender age at which language is typically learned, suggests that infants must come to the task of language acquisition already possessing the machinery required to master human language. What remains unknown is the nature of this machinery. Do infants possess dedicated domain-specifi c learning mechanisms, evolved for language acquisition? Or do infants take advantage of existing learning mechanisms that are not domain-specifi c to discover the structure of human language? In this chapter, we will consider the current state of the art in disentangling these views. While some progress has been made since Chomsky’s (1959) quotation reprinted above, much still remains unknown.

L'A. examine de maniere critique l'hypothese de Rhode et Plaut selon laquelle l'apprentissage de la structure d'une langue naturelle est possible en depit du manque d'une retroaction negative explicite en l'absence de mecanismes innes precis de l'acquisition du langage