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Multimodal sentiment classification is a notable research field that aims to refine sentimental information and classify the sentiment tendency from sequential multimodal data. Most existing sentimental recognition algorithms explore multimodal fusion schemes that achieve good performance. However, there are two key challenges to overcome. First, it is essential to effectively extract inter- and intra-modality features prior to fusion, while simultaneously reducing ambiguity. The second challenge is how to learn modality-invariant representations that capture the underlying similarities. In this paper, we present a modality-invariant temporal learning technique and a new gated inter-modality attention mechanism to overcome these issues. For the first challenge, our proposed gated inter-modality attention mechanism performs modality interactions and filters inconsistencies from multiple modalities in an adaptive manner. We also use parallel structures to learn more comprehensive sentimental information in pairs (i.e., acoustic and visual). In addition, to address the second problem, we treat each modality as a multivariate Gaussian distribution (considering each timestamp as a single Gaussian distribution) and use the KL divergence to capture the implicit temporal distribution-level similarities. These strategies are helpful in reducing domain shifts between different modalities and extracting effective sequential modality-invariant representations. We have conducted experiments on several public datasets (i.e., YouTube and MOUD) and the results show that our proposed method outperforms the state-of-the-art multimodal sentiment categorization methods. • Proposing a modality-invariant temporal representation learning strategy. • Designing GIMA to adaptively filter inconsistencies between modalities. • Designing a Transformer-based parallel structure for modality-interactions. • Reaching the state-of-the-art for multimodal sentiment recognition on four datasets. [ABSTRACT FROM AUTHOR]

Cross-domain classification with small samples is a more challenging and realistic experimental setup. Until now, few studies have focused on the problem of small-sample cross-domain classification between completely different hyperspectral images (HSIs) since they possess different land cover types and statistical characteristics. To this end, this paper proposes a general-purpose representation learning method for cross-domain HSI classification, aiming to enable the model to learn more general-purpose deep representations that can quickly adapt to different target domains with small samples. The core of this method is to propose a novel three-level distillation strategy to transfer knowledge from multiple models well-trained on source HSIs into a single distilled model at the channel-, feature- and logit-level simultaneously. The learned representations can be further fine-tuned with small samples and quickly adapt to new target HSIs and previously unseen classes. Specifically, to transfer and fuse knowledge from multiple-source domains into a single model simultaneously and solve the inconsistency of the number of bands in different HSIs, an extensible multi-task model, including the channel transformation module, the feature extraction module and the linear classification module, is designed. Only the feature extraction module is shared across different HSIs, while the other two modules are domain-specific. Furthermore, the typical episode-based learning strategy of the metric-based meta-learning is adopted in the whole learning process to further improve the generalization ability and data efficiency. Extensive experiments are conducted on six source HSIs and four target HSIs, and the results demonstrate that the proposed method outperforms the existing advanced methods in cross-domain HSI classification with small samples. [ABSTRACT FROM AUTHOR]

Deep learning based image quality assessment models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes. To account for this, mixed datasets training can be an effective way to enhance the generalization capability of the model. However, it is nontrivial to combine different image quality assessment datasets, as their quality evaluation criteria, score ranges, view conditions, as well as subjects are usually not shared during the image quality annotation. Instead of aligning the annotations, this paper proposes a monotonic neural network for image quality assessment model learning with different datasets combined. In particular, this model consists of a dataset‐shared quality regressor and several dataset‐specific quality transformers. The quality regressor aims to obtain the perceptual quality of each image of each dataset and the quality transformer maps the perceptual quality to the corresponding annotation monotonically. The experimental results verify the effectiveness of the proposed learning strategy and the code is available at https://github.com/fzp0424/MonotonicIQA. [ABSTRACT FROM AUTHOR]

Accurate estimation of State of Health (SOH) is crucial to ensure optimal performance and safe operation of lithium-ion battery. This paper proposes a Stacking ensemble learning paradigm for SOH estimation. The Stacking ensemble learning increases adaptability to different features by using base learners with different structures, reducing the risk of overfitting. The model utilizes random vector functional link (RVFL) and active state tracking long-short-term memory network (AST-LSTM) as base learners, where AST-LSTM actively tracks long-term information of lithium-ion battery, and RVFL acts as the meta-learner for stacking. The random vector functional link network helps to avoid the problem of gradient vanishing that is commonly encountered in neural networks due to the gradient descent principle. To further improve estimation accuracy, Singer initialization method and dimension learning method are employed to enhance the Heap-based optimization (HBO) algorithm. In this study, the IHBO algorithm is used to optimize the hyperparameters of the model. Comparing with other methods, the hybrid model proposed in this paper demonstrates superior estimation performance under different operating conditions: at a temperature of 24 °C with a discharge current of 1 A, at a temperature of 4 °C with a discharge current of 1 A, and at a temperature of 4 °C with a discharge current of 2 A. The highest RMSE of the proposed method for the three working conditions are 0.006, 0.01, and 0.017, respectively. Therefore, the proposed Stacking ensemble learning is feasible for SOH estimation of lithium-ion battery and can better adapt to lithium-ion battery data under different operating conditions. • A Stacking ensmeble learning strategy is proposed for SOH estimation. • The improved HBO algorithm is introduced to optimize the Stacking model. • SOH for lithium batteries under three different operating conditions is estimated. • Six benchmark models are used to verify the performance of the proposed model. [ABSTRACT FROM AUTHOR]

Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone to suffer the consequences of data statistical heterogeneity, both across the different entities and over time, which may lead to a lack of convergence. To avoid such issues, different methods have been proposed in the past few years. However, data may be heterogeneous in lots of different ways, and current proposals do not always determine the kind of heterogeneity they are considering. In this work, we formally classify data statistical heterogeneity and review the most remarkable learning Federated Learning strategies that are able to face it. At the same time, we introduce approaches from other machine learning frameworks. In particular, Continual Learning strategies are worthy of special attention, since they are able to handle habitual kinds of data heterogeneity. Throughout this paper, we present many methods that could be easily adapted to the Federated Learning settings to improve its performance. Apart from theoretically discussing the negative impact of data heterogeneity, we examine it and show some empirical results using different types of non-IID data. • We review the advances in Federated Learning, particularly on heterogeneous data. • We consider time-evolving situations in Federated Learning. • We establish a classification of the literature according to their data heterogeneity. • We settle restrictions inherent to some of the problem scenarios. • We examine the open challenges and future directions for Federated Learning. [ABSTRACT FROM AUTHOR]

Background: A growing body of research demonstrates that adapting the popular entertainment activity "escape rooms" for educational purposes as an innovative teaching method can improve the learning experience. Escape rooms promote teamwork, encourage analytical thinking, and improve problem solving. Despite the increasing development and use of escape rooms in health sciences programs and academic libraries, there is little literature on the use of this method in health sciences libraries with health professions students. Case Presentation: Staff at a health sciences library collaborated with faculty to incorporate escape rooms into library instruction in a variety of settings (in-person, hybrid, online) and formats (team, individual) with health professions students from various disciplines (optometry, pharmacy, medicine). The escape rooms described in this paper offered unique experiences for students through active learning. Discussion: Important considerations when planning escape rooms for health sciences library instruction include deciding on team-based or individual design, calculating potential costs in time and money, deciding on an in-person, hybrid, or online format, and determining whether grades should be assigned. Escape rooms can be an effective strategy for library instruction in the health sciences, working in multiple formats to bring game-based learning to a variety of health professions students. [ABSTRACT FROM AUTHOR]

Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. Existing methods mainly focus on learning modality-shared representations by embedding images from different modalities into a common feature space, in which some discriminative modality information is discarded. Different from these methods, in this paper, we propose a novel Modality-Specific Memory Network (MSMNet) to complete the missing modality information and aggregate visible and infrared modality features into a unified feature space for the VI-ReID task. The proposed model enjoys several merits. First, it can exploit the missing modality information to alleviate the modality discrepancy when only the single-modality input is provided. To the best of our knowledge, this is the first work to exploit the missing modality information completion and alleviate the modality discrepancy with the memory network. Second, to guide the learning process of the memory network, we design three effective learning strategies, including feature consistency, memory representativeness and structural alignment. By incorporating these learning strategies in a unified model, the memory network can be well learned to propagate identity-related information between modalities and boost the VI-ReID performance. Extensive experimental results on two standard benchmarks (SYSU-MM01 and RegDB) demonstrate that the proposed MSMNet performs favorably against state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Separating the dominant person from the complex background is significant to the human-related research and photo-editing based applications. Existing segmentation algorithms are either too general to separate the person region accurately, or not capable of achieving real-time speed. In this paper, we introduce the multi-domain learning framework into a novel baseline model to construct the Multi-domain TriSeNet Networks for the real-time single person image segmentation. We first divide training data into different subdomains based on the characteristics of single person images, then apply a multi-branch Feature Fusion Module (FFM) to decouple the networks into the domain-independent and the domain-specific layers. To further enhance the accuracy, a self-supervised learning strategy is proposed to dig out domain relations during training. It helps transfer domain-specific knowledge by improving predictive consistency among different FFM branches. Moreover, we create a large-scale single person image segmentation dataset named MSSP20k, which consists of 22,100 pixel-level annotated images in the real world. The MSSP20k dataset is more complex and challenging than existing public ones in terms of scalability and variety. Experiments show that our Multi-domain TriSeNet outperforms state-of-the-art approaches on both public and the newly built datasets with real-time speed. [ABSTRACT FROM AUTHOR]

Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain strategies are used. In other words, all of the existing frameworks lack an important step, that is, result confirmation. In this paper, we propose a Result Confirmation-based Learning Behavior Analysis (ReCoLBA) framework, which adds a result confirmation step for exploring the hidden reasons underlying the learning patterns and strategies. Using this ReCoLBA framework, a case study was conducted which analyzed e-book reading data. In the case study, we found that the students had a tendency to delete markers after adding them. Through an investigation, we found that the students did this because they could not grasp the learning emphasis. To apply this finding, we proposed a learning strategy whereby the teacher highlights the learning emphasis before students read the learning materials. An experiment was conducted to examine the effectiveness of this strategy, and we found that it could indeed help students achieve better results, reduce repetitive behaviors and save time. The framework was therefore shown to be effective. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to assess the most commonly used L2 learning strategies, especially those of communicative type, of undergraduate students and how these strategies are related to their language performance. Additionally, this study also aims to examine the effect of gender on the type of strategies they use and how this fact affects learning. We make a comparative study of the use of L2 learning strategies by Spanish undergraduates and by those coming from the Erasmus+ program and from the Republic of Korea. In terms of data collection, two instruments have been used, a self-made profile questionnaire and the SILL inventory (Oxford, 1990), in order to evaluate students' use of L2 learning strategies, data on the similarities and differences in the use and level of frequency of use of strategies employed by our students. Furthermore, the emerging profile of the data analysis obtained has been described and we have made an assessment by comparing our data with that of previous research. In addition, we also find that gender is a significant factor among all students regardless their nationalities. We discover that the female students make a greater use and with more frequency of all type of learning strategies, especially those of communicative type, with special relevance in the socio-affective strategies. In our conclusion, we point out that training in learning strategies for second language acquisition can help learners learn better by increasing their awareness of L2 learning strategies, and by increasing the number of strategies they use. Moreover, knowing the L2 learning strategies used by our students becomes a guarantee of success when designing teaching methodologies aimed at achieving significant learning results. [ABSTRACT FROM AUTHOR]

The Malaysian government's ongoing movement control order (MCO) to prevent coronavirus disease 2019 (COVID-19) spread, has disrupted the teaching and learning (T&L) activities of higher education institutions in the country. This paper seeks to outline the steps taken by the Department of Family Medicine of the International Medical University (IMU), Malaysia, to adapt its online teaching and learning activities. The five tips are: i) understand how to use online T&L platforms; ii) teachers should create multiple communication channels; iii) ensure attendance is captured; iv) enhance the online T&L experience and v) conduct online formative assessments. [ABSTRACT FROM AUTHOR]

The developmental origins of synaesthesia have only recently become the focus of serious scientific research. Most existing theories posit a simple genetic mutation as the primary causal factor in synaesthetic development, but it is widely recognized that a complete theory will have to involve learning in some manner. Our paper presents the developmental learning hypothesis (DLH) of synaesthesia, which, as the name suggests, treats learning as a central component of the development of synaesthesia. According to the DLH, synaesthesia arises, at least in part, as a strategic response to specific learning challenges faced in childhood. The paper focusses on grapheme-colour synaesthesia, in which individuals associate specific colours with letters and numerals. We describe a number of the problems faced by children becoming literate, ranging from learning to identify individual letters to learning to keep phonemes in the correct order when reading, and illustrate ways in which grapheme-colour synaesthesia might be helpful in solving these problems. [ABSTRACT FROM AUTHOR]

The social distance caused by the COVID-19 pandemic has resulted in the suspension of face- to-face classes around the world. Educational methods needed to be quickly adapted to the remote learning. This unexpected adaptation impacted students and teachers who, together, committed themselves to experimenting new forms of teaching and learning in order to maintain the continuity of teaching, research and extension activities. Therefore, the goal of this paper is to describe the process of adapting a university extension project to the remote learning. It is also proposed to share experiences and learnings that can contribute to the design of new pedagogical strategies that provide the student's autonomy in the learning process in this new pandemic reality. [ABSTRACT FROM AUTHOR]

The different learning methodologies of higher education stood out in the last decades, in the sense of breaking the barriers of traditional teaching, purely expository and protagonized in the person of the teacher. In the defense of more active and transdisciplinary methods, this paper aims to associate, classify and understand andragogical practices – teaching and learning strategies developed for adults – through the film analysis of the Dead Poets Society. [ABSTRACT FROM AUTHOR]

This paper presents a review about the learning of writing. It integrates relevant contributions from fields of Psychology, Linguistics and Semiotics during the last 30 years. We begin by addressing different aspects of writing as a semiotic object and synthesize its uses and functions within a culture. Writing functions as a mnemonic tool through graphic representation, allowing preservation, transmission and modifi-cation of collective shared knowledge, enabling its functioning as an epistemic tool. Writing also has regulatory functions on social behavior. It contrib - utes to the organization of social roles and the establishment of hierarchical order through the enactment of written laws. It also contributes to the standardization of a linguistic variety -the one used for writing- in order to fulfill several official functions related to public administration and edu - cation. Consequently, the linguistic variety repres ented in writing usually becomes a linguistic model, outlining diverse social and personal paths in learning to write. Finally, we focus on its aes - thetic and imaginative function, which is present in a variety of genres. We then describe the attributes of writing as a semiotic system, including written texts' distinctive features according to their functions in certain situational and socio-cultural settings. All writing systems have a dual nature: they constitute physical objects with an external existence that is relatively independent from its context of production, also are semiotic objects that enable to represent something else. In writing systems, a set of graphic elements are integrated on a surface. Rules conventionally established and formal properties are the base of these graphic elements. These graphic marks en - dure through time and space, allowing for iterative formal and conceptual revision and change. A dialectic relationship between mind and semiotic system is established, in which representational systems, as external scaffolding, expanding the possibilities of thought. Thereby, this technology of thought entails important cognitive and social transformations by helping to construct a multiple and broadening personal perspective. This will allow the con ver - sion of own representations into meta- representations through their externalization, and the ac - quirement of new and more complex ways of knowing. In the second part of this article, we tackle relevant characteristics of learning to write along a person's life. This process begins almost from birth and continues through adult life, under the guide of someone with more expertise. Becoming an expert writer requires more than two decades of continuo - us instruction and practice. The appro priation of writing requires processes correlated at multiple cognitive dimensions and linguistic levels, deeply related to specific contexts of use. The dimensions considered are the following: meta knowledge; general knowledge about writing; specific know - ledge regarding graph phonic, syntactic, and textual aspects; and procedural knowledge. We review studies regarding the different dimensions involved in this process from a developmental and educat - ional perspective. We organize such review by considering three moments. The stage named roots of literacy comprises all the activities and concept - ualizations of reading and writing that children carry out in the course of early childhood, which precedes conventional literacy. During schooling writing becomes a learning object, and children's main efforts move from mastering the alphabetic code to understanding coherence and cohesion, as well as producing texts of several types. When referring to learning to write during schooling we also focus on learners' conceptions of this process. The conceptions' viewpoint enables us to under - stand the learners' own perspective displayed in first person. Beyond schooling learning to write continues developing towards the ability of constructing and reconstructing knowledge through reading and writing. Finally, we analyze contrib - utions on learning to write from a multimodal perspective. We acknowledge a research vacancy which would articulate learners' resources for text production and their conceptions about this process. Based on the idea that learning entails unfolding a variety of resources -particularly semiotic and epistemic- in a situated and contextualized manner, we propose that an articulation among the different approaches reviewed in this paper will help to overcome the deficit perspectives. [ABSTRACT FROM AUTHOR]

In the past decades, various systems have been proposed to provide students with a better learning environment by taking personal factors into account. Learning styles have been one of the widely adopted factors in the previous studies as a reference for adapting learning content or organizing the content. However, very few researchers give an idea of matching e-media with appropriate teaching and learning styles and very few studies give an idea of which appropriate combinations of electronic media and learning styles are more effective than other. In this paper, the authors aim to prototype an AFDPC-FS system (Adaptation with Four Dimensional Personalization Criteria based on Felder Silverman model). Their system presents a general framework for combining and adapting teaching strategies, learning styles and electronic media according to Felder-Silverman's learning style model. An experiment was designed to explore the effect of adaptation to different learning styles when learning materials were matched with learning styles. In particular it was set up to see whether there are significant differences in learning achievement and cognitive load between two groups, an experimental group who studied with learning style-fit version and a control group who studied with non-fit version of the system without adaptation to learning styles. The experimental results showed that the proposed system could improve the learning achievements of the students. Moreover, it was found that the students' cognitive load was significantly decreased. [ABSTRACT FROM AUTHOR]

This paper presents the partial results of a research project where the incidence that the multigraduate rural school has on its students was studied, within the framework of a phenomenological qualitative paradigm, resulting in a first exploratory study on the conceptions, motivations and learning strategies of the students, according to the model on learning factors (SAL). The submitted results refer to the meanings that the students infer regarding three variables related to their learning, based on the answers given in semistructured interviews and the analysis of the ideas underlying their content. With regard to the conception of learning, the results show that students play an important role in their socialization function; furthermore, the importance of classmates and the relationships between them are considered keys to a successful learning. On the other hand, in reference to learning strategies, the individualistic vision of the students is significant, considering learning as a personal and non-transferable process of each of them, which does not, then, hang together with what has been expressed previously. Concerning motivation for learning, a study-prize relationship of a superficial approach to learning predominates. [ABSTRACT FROM AUTHOR]

Contextual learning starts from the premise that learning cannot take place in a vacuum, but should somehow be connected with real world attributes to make sense to learners. Today, digital media tend to bring about new dimensions of context: internet connections and mobile devices enable learners to overcome restrictions of time and location, and neglect the physical boundaries and limitations of the learning environment. This calls for reconsidering contextual learning. This paper takes a theoretical stand by conceptualising the notion of learning context in the light of its virtualised extensions. It explains the historical and pedagogical backgrounds of contextual learning and reviews existing models that deal with context parameters. The paper identifies and discusses the constituting components of context for learning and it demonstrates how attributes of virtual representations affect the nature of context. The overall purpose of the paper is re-establishing the notion of contextual learning in the light of emerging digital media and making explicit the various dimensions involved. [ABSTRACT FROM AUTHOR]

Current research work in e-learning and more specifically in the field of CSCL (Computer Supported Collaborative Learning) deals with design of collaborative activities, according to computer-interpretable specifications, such as IMS Learning Design, and their posterior enactment using LMSs (Learning Management Systems). A script that describes such collaborative activities is typically designed beforehand in order to structure collaboration, and defines the features that determine the behavior of the LMS, for instance, the sequence of activities or the groups/role distribution. In CSCL settings, group management and composition are especially relevant and affect the chances of achieving the expected learning outcomes. This paper presents a software tool, named Instance Collage, which aims at facilitating the configuration and population of groups for IMS-LD scripts created with the authoring tool Collage, and discusses the implications of the IMS-LD specification with respect to this task. InstanceCollage is designed to process collaboration scripts based on CLFPs (Collaborative Learning Flow Patterns). Using this type of patterns, InstanceCollage focuses on the importance of understanding the function of groups within the learning strategy of the script. This paper describes the approach taken in InstanceCollage to facilitate this understanding for non-expert users. Additionally, two case studies are presented, which represent complex authentic collaborative learning scenarios, as a proof of concept of the functionality of this tool. The case studies are also used to illustrate the requirements of group configuration tools and to show that InstanceCollage complies to such requirements. [ABSTRACT FROM AUTHOR]

This paper describes a computer-supported collaborative learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on free- and open-source software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. The Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates on how Collage and Gridcole were employed, describes the applied evaluation methodology, and discusses the most significant findings derived from the case study. [ABSTRACT FROM AUTHOR]

The transition process from building a minimum knowledge base to deploying the first strategic capabilities is a neglected issue in the literature on technological accumulation in Latin American firms. This paper analyses three organisational processes that may affect this stage and discusses the role of an unstable firm's technology strategy in influencing such processes. Based on a detailed case study of Vitro S.A., one of the largest and most successful Mexican industrial groups, this paper argues that a context characterised by macroeconomic instability and distortions, and the lack of vision of the firm's top management about the role of technology in competitiveness, contribute to explaining the instability of the firm's technology strategy. This, in turn, is a major factor that negatively influences the conversion of individual into organisational learning, the coordination of different learning strategies, and the steadiness of the knowledge-creation process. The weaknesses in these processes make the deployment of strategic capabilities and the completion of the transition process more difficult. [ABSTRACT FROM AUTHOR]

This paper describes how research into approaches to university teaching, from a relational perspective, has been used to develop an inventory to measure the key aspects of the variation in approaches to teaching. The Approaches to Teaching Inventory (ATI) is one of several that derive from the research perspective applied by Marton and colleagues in Europe (Marton, F., Hounsell, D., and Entwistle, N. (eds.) (1997). The Experience of Learning, 2nd edn., Scottish Academic Press, Edinburgh) to student learning. A feature of these inventories is that they measure the response of a group to a particular context, rather than more general characteristics of individuals in that group. Studies using these inventories have consistently shown relations between students’ approaches to learning and the quality of their learning outcome. The question of interest to many university teachers is whether there are relations between the way teachers approach their teaching and ways their students approach their learning. This question was answered in a study published in 1999 that used the ATI to show that teacher-focused approaches to teaching were associated with students’ reproducing orientations. Subsequent research revealed that in subjects where teachers adopted more student-focused approaches to teaching, their students adopted a deeper approach to learning. Some recent research using the inventory is reviewed along with an analysis of the validity of the ATI. The current version of the inventory is reproduced in this paper. [ABSTRACT FROM AUTHOR]

The aim of this paper is to explore empirically the learning potential of people with schizophrenia in opposite conditions of psychopathological stability. For this purpose, a general procedure of conditional discrimination learning was introduced by conducting a study on the formation of equivalence classes. The sample consisted of 8 inpatient adults included in the program of Severe Mental Disorders, aged between 20 and 53 years. Because of dropouts, the initial procedure was modified in order to reduce the duration and attentional effort of the task. The results showed that people with schizophrenia can acquire stimulus equivalence with standard procedure both in terms of stability and psychopathological decompensation, in the presence of strong positive symptoms. This finding is relevant both for therapy, conceived in terms of learning, and for designing programs in the context of rehabilitation and recovery in schizophrenia. [ABSTRACT FROM AUTHOR]

Background: Growing demand for Global Health (GH) training and the internationalisation of education requires innovative approaches to training. Blended learning (BL, a form of e-learning combining face-to-face or real-time interaction with computer-assisted learning) is a promising approach for increasing GH research capacity in low- to middle-income countries. Implementing BL, however, requires additional skills and efforts from lecturers. This paper explores lecturers' views and experiences of delivering BL courses within the context of two north-south collaborative research capacity building projects, ARCADE HSSR and ARCADE RSDH. Design: We used a qualitative approach to explore the experiences and perceptions of 11 lecturers involved in designing and delivering BL courses collaboratively across university campuses in four countries (South Africa, Uganda, India and Sweden). Data were collected using interviews in person or via Skype. Inductive qualitative content analysis was used. Results: Participants reported that they felt BL increased access to learning opportunities and made training more flexible and convenient for adult learners, which were major motivations to engage in BL. However, despite eagerness to implement and experiment with BL courses, they lacked capacity and support, and found the task time consuming. They needed to make compromises between course objectives and available technological tools, in the context of poor Internet infrastructure. Conclusions: BL courses have the potential to build bridges between low- and middle-income contexts and between lecturers and students to meet the demand for GH training. Lecturers were very motivated to try these approaches but encountered obstacles in implementing BL courses. Considerable investments are needed to implement BL and support lecturers in delivering courses. [ABSTRACT FROM AUTHOR]

Teaching and learning environments of software process improvement are incorporating new strategies for helping to decrease current weaknesses related to basic-sciences formation, motivation, and communication. One of such strategies includes the usage of gamification principles for achieving student competencies related to teamwork, problem solving, leadership, and effective communication. For assessing the teaching and learning strategies, it is required to consider the following features: i) the student competencies; ii) the didactic proposals and techniques; and, iii) the satisfaction level of the students, regarding the teaching strategy. In this paper, an assessment proposal of teaching and learning strategies in software process improvement is presented, with a preliminary validation method based on gamification principles. Finally, a case study for validating a didactic proposal is presented as a pilot of the assessment proposal. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to present how in the Environments of Personalized Learning for the careers of agricultural profile the information can be recovered by the application of the techniques of Mining of Processes. It is started from the identification of common aspects among the concept of unit of learning of the standard IMS-LD, the pattern of data XES and social graph ontology. Are show up the main advances in the area of the Environments of Personalized Learning as well as some elements of the didactics that base the learning in systems centered in the student. Are described some concepts defined in the ontology, which can be used to develop computer systems that support those scenarios. The vocabulary was defined reutilizing FOAF and the OpenSocial specifications. By means of the concept of Activity defined in the ontology and of their relationships, are represented the events of the social nets as those that compose a unit of learning compatible with IMS-LD. It is explained how managing the similarity among the concepts defined in IMS-LD and the pattern of XES data is possible to apply the techniques of the Mining of Processes to discover learning models, patterns of activities and to carry out social mining. By way of example it is shown how in a learning unit you can apply the technique of Alignment of Appearances to detect possible learning patterns. [ABSTRACT FROM AUTHOR]

In this paper, we studied mission planning problem for Earth observation satellites using a competitive learning strategy. In particular, a scheme based on Q-network is proposed to solve scheduling problem of a single satellite, while a profit-based competitive strategy is introduced to address the scheduling conflict problem inherent with multi-satellite missions. More specifically, the Q-network is integrated with the competitive strategy to improve the algorithmic scalability and to reduce the communication burden, and the search-window is designed to improve scheduling efficiency by eliminating the obvious unbefitting choices in the learning process. Simulation results verified the performance of the proposed schemes. [ABSTRACT FROM AUTHOR]

This research paper presents a study aimed to determine the relationship between learning styles and strategies in the Universidad de Sucre (Colombia) Health Science students. The learning style preference was identified using the Scale Learning Strategies for College Students (ACRA De la Fuente and Justicia-Justicia). The relation between variables was observed with the Pearson coefficient of interrelation (significancia p:0.05). Results showed independence between learning styles and learning strategies within this career. No direct correlation was found between a style and any specific strategy. [ABSTRACT FROM AUTHOR]

This paper provides information about the efficacy of a tutorial training program intended to enhance elementary fifth graders' study processes and foster their deep approaches to learning. The program «Testas's (mis)adventures» consists of a set of books in which Testas, a typical student, reveals and reflects upon his life experiences during school years. These life stories are nothing but an opportunity to present and train a wide range of learning strategies and self-regulatory processes, designed to insure students' deeper preparation for present and future learning challenges. The program has been developed along a school year, in a one hour weekly tutorial sessions. The training program had a semi-experimental design, included an experimental group (n=50) and a control one (n=50), and used pre- and posttest measures (learning strategies' declarative knowledge, learning approaches and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge of learning strategies and in their deep approach to learning, consequently lowering their use of a surface approach. In spite of this, in what concerns to academic achievement, no statistically significant differences have been found. [ABSTRACT FROM AUTHOR]

We propose Lifelong Learning Organisers (LLOs) as tools to support the capturing, organisation and retrieval of personal learning experiences, resources and notes, over a range of learning topics, at different times and places. The paper discusses general requirements for the design of LLOs based on findings from a diary-based study of everyday learning practice; and also based on the design and evaluation of KLeOS, a prototype LLO that supports learning projects, episodes and activities through the linking of learning content with semantic and episodic context. We suggest that LLOs should assist in capturing both the episodic and the semantic aspects of learning events, and should incorporate retrieval mechanisms that utilise both types of memory (i.e. episodic and semantic) to assist tracing back knowledge and resources. Issues for future research on LLOs are also discussed. [ABSTRACT FROM AUTHOR]

This paper discusses the results of the Learning and Study Strategies Inventory (LASSI) administered to college students in order to identify similarities and differences between time of diagnosis of a learning disability and the development of learning strategies related to will, sell=regulation, and skill components. Findings indicate that early identification (in K-12) and providing students with test-taking strategies may ameliorate academic success in higher education for students with learning disabilities. Recommendations for action will assist developmental educators to better serve college students with learning disabilities in higher education. [ABSTRACT FROM AUTHOR]

This paper presents the Model of Strategic e-Learning to explain and evaluate student e-learning from metacognitive perspectives. An in-depth interview, pilot study and main study are employed to construct the model and develop an instrument-the Online Learning Strategies Scale (OLSS). The model framework is constructed and illustrated by four dimensions of characteristics of e-learning environments and three core domains (perceived-skill, affection and self-regulation) of student e-learning strategies. This study also tries to identify and analyze elements corresponding to each domain strategy. Based on this model, the OLSS finally contains 20 items with good construct validity and reliability. This instrument provides a diagnostic instrument for e-learning researchers, system designers, curriculum developers and instructors to evaluate students' e-learning strategies in their experiment, design and development. This study concludes by presenting several future research directions. [ABSTRACT FROM AUTHOR]

In this special issue, we focus on critical issues associated with organisational learning involving external sources, with particular emphasis on the process of external learning and its implications on firm performance. The papers that constitute this special issue are eclectic, yet an interrelated mix of conceptual, exploratory research, and empirical research that examine several key aspects of learning from external sources. In this introductory article, we synthesise the key issues for pursuing an external learning strategy, discuss the contributions that this special issue makes to the literature that addresses these issues, and offer a framework for guiding further theory development, and empirical research. [ABSTRACT FROM AUTHOR]

In this paper, we present a model which describes the main elements and aspects of teaching and learning in pharmacy education. We first explore what quality of teaching and learning means. From this information, we concentrate on pedagogical implications to change pharmacy teaching to improve the quality of learning. In the final section, we summarise the importance of developing the pharmacy teaching due to the demands of Bologna process, lifelong learning in working life, and university staff development. [ABSTRACT FROM AUTHOR]

This paper reviews the research conducted in the last decade on patterns in student learning, mostly in higher education. More specifically, the review focuses on a series of studies that have in common (a) the use of the Inventory of Learning Styles (ILS), an instrument aimed at measuring several components of student learning, namely, cognitive processing strategies, metacognitive regulation strategies, conceptions of learning, and learning orientations; and/or (b) an integrative learning theory focussing on the interplay between self-regulation and external regulation of learning processes as a theoretical framework. Aspects a and b are closely connected, because the development of the instrument was based on the theory. The review covers the following themes: The theoretical framework and conceptualization of student learning; a description of the instrument; the internal structure of learning strategies, conceptions, and orientations in different educational contexts; developments in learning patterns during the school career; consistency and variability in students’ use of learning strategies; dissonance in students’ regulation of learning processes; relations between learning patterns and personal and contextual factors; relations between learning patterns and learning outcomes; and process-oriented instruction. [ABSTRACT FROM AUTHOR]

Background: User understanding of information technology systems (IT-Systems) is a prerequisite for their use. This study aimed to explore how primary care physician trainees learn, understand and use IT-Systems.Methods: A paper-based survey study among 301 primary care physician trainees in Baden-Wuerttemberg, Germany, was performed. The questionnaire included measures of understanding and use of nine specific system features, five possible learning strategies, a validated scale for affinity for technology interaction, and five individual and three practice characteristics.Results: The sample comprised 94 respondents (31.6% response rate). Between 3.2 and 59.6% said to know specific systems features well; between 13.8 and 42.6% expressed a wish to know more about specific system features. The predominant strategy for learning system features was explanation by others: 51.7 to 66.7% had applied this strategy to learn the features. Between 18.6 and 41.4% had learned the features by trial and error. A better understanding of system features was associated with the use of a trial and error strategy for learning system features (beta = 0.260, p = 0.012). The use of a greater variety of learning strategies was associated with higher affinity for technology interaction (beta = 0.215, p = 0.037).Conclusion: The study suggests that many physicians need a better understanding of IT-Systems. The role of manuals, online resources and courses in learning IT-Systems seems limited. The new generation of primary care physicians seem to learn features of IT-Systems through explanation by others and trying in their ambulatory practices. The relevance of IT-Systems in healthcare is high, but physicians need more support in learning to use system features. [ABSTRACT FROM AUTHOR]

The introduction of video games in education has raised a number of possibilities, but also problems and doubts about the true potential. This built-in progressive scan the classroom process has put on the table a number of problematizations about how and why you can use video games to teach. The purpose of this paper is to make a small mapping on the subject, where we board the notion of serious games and some educational experiences that have used these tools in educational contexts. Finally, we put some basic notions about the possibilities of teaching with video games and raising some reviews and thoughts on the way forward in the coming years. [ABSTRACT FROM AUTHOR]