Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learning by doing. In two classroom experiments, we found that students who explained their (...) steps during problem‐solving practice with a Cognitive Tutor learned with greater understanding compared to students who did not explain steps. The explainers better explained their solutions steps and were more successful on transfer problems. We interpret these results as follows: By engaging in explanation, students acquired better‐integrated visual and verbal declarative knowledge and acquired less shallow procedural knowledge. The research demonstrates that the benefits of self‐explanation can be achieved in a relatively simple computer‐based approach that scales well for classroom use. (shrink)

Drug abuse has been and continues to be, a common social issue worldwide, yet the efficiency of widely adopted sweeping speech for anti-drug campaigns has proven inefficient. To provide students with a safe and efficient learning situation related to drug refusal skills, we used a novel approach rooted in a serious learning game and concept map during a brief extracurricular period to help students understand drugs and their negative effects. The proposed game-based situational learning system allowed all (...) students to participate simultaneously and individually in multiple scenarios of drug temptation posed by peers and classmates to practice responding and refusing drugs in school and community settings. Moreover, to explore whether different personality traits result in different anti-drug responses, we used a serious game to conduct an anti-drug experiment on 53 junior middle school students aged 13–15. Each participant’s decision-making process was recorded in the serious game as behavioral patterns for lag sequential analysis. The outcomes revealed seven behavioral patterns including differentiation, acceptance, effective and ineffective responses, effective and ineffective solution-seeking, and failure to refuse. The GSEQ which is a computer program for analyzing sequential observational data was used. The results indicated the following: Neuroticism was performed at a relatively low level under the guidance of a concept map. “Neuroticism” was associated with the lowest risk of accepting drugs. Students with “openness to experiences” were at high risk of accepting drugs. Almost all personality behavioral transition diagrams showed that failure to refuse drugs was followed by inefficient seeking of help and inefficient refusal. These findings provide reference points for designing adaptive anti-drug education programs. (shrink)

Design based research has been acknowledged as a productive approach for advancing educational technology. Coincidentally, open source software has been found to be a good fit for implementing design based research. This report presents a case study of a software project using a design-based research approach and free/open source software. The project, iSocial, is developing a 3D virtual environment for youth with autism spectrum disorders to develop social competence. The study illustrates how the flexibility and community features of FOSS fit (...) with the iterative nature of design-based research to benefit the development of iSocial, and the report also discusses challenges of implementing FOSS and DBR. (shrink)

This article shows the organization of distance learning, particularly the idea of b-learning, combining the accomplishment of classes carried on in the traditional way and via computers. The authors present learning activities related to complementary education herein. Some of these course types may be successfully adapted to an e-learning background. The models and structure of the university virtual environment for distance learning are described. These illustrate a new approach to creating a virtual space for medical (...) and technical studies where e-learning courses are created to be used for distance education, which allows students to be taught more effectively. The projected virtual courses for different groups of students ensure individualization of students’ work, which could be a relevant element for creating the shortest path of development of professional competencies. This paper further includes a brief overview of technologies used to build interactive elements into learning mate- rials. The authors present the use of interactive elements in medical education based on examples of certain selected games and animations. (shrink)

Context: The advent of a general artificial intelligence mechanism that learns like humans do would represent the realization of an old and major dream of science. It could be achieved by an artifact able to develop its own cognitive structures following constructivist principles. However, there is a large distance between the descriptions of the intelligence made by constructivist theories and the mechanisms that currently exist. Problem: The constructivist conception of intelligence is very powerful for explaining how cognitive development takes place. (...) However, until now, no computational model has successfully demonstrated the underlying mechanisms necessary to realize it. In other words, the artificial intelligence (AI) community has not been able to give rise to a system that convincingly implements the principles of intelligence as postulated by constructivism, and that is also capable of dealing with complex environments. Results: This paper presents the constructivist anticipatory learning mechanism (CALM), an agent learning mechanism based on the constructivist approach of AI. It is designed to deal dynamically and interactively with environments that are at the same time partially deterministic and partially observable. CALM can model the regularities experienced in the interaction with the environment, on the sensorimotor level as well, as by constructing abstract or high-level representational concepts. The created model provides the knowledge necessary to generate the agent behavior. The paper also presents the coupled agent environment system (CAES) meta-architecture, which defines a conception of an autonomous agent, situated in the environment, embodied and intrinsically motivated. Implications: The paper can be seen as a step towards a computational implementation of constructivist principles, on the one hand suggesting a further perspective of this refreshing movement on the AI field (which is still too steeped in a behaviorist influence and dominated by probabilistic models and narrow applied approaches), and on the other hand bringing some abstract descriptions of the cognitive process into a more concrete dimension, in the form of algorithms. Constructivist content: The connection of this paper with constructivism is the proposal of a computational and formally described mechanism that implements important aspects of the subjective process of knowledge construction based on key ideas proposed by constructivist theories. (shrink)

CASUS is an authoring system, which should enable physicians to produce problem-based computer learning programs with minimal technical effort and give them sound instructional support. The theoretical background of CASUS are constructivist approaches to learning and instruction, which deal mainly with the question, how to design problem-based learning environments. The paper presents the constructivist concept of CASUS and results of a forma-tive evaluation. Four authors were observed and interviewed while developing a learning case with CASUS. (...) The evaluation pursued mainly the question of which difficulties arise while producing a case with CASUS and which measures are necessary in order to improve the authoring system. Results show that with regard to technical aspects physicians can produce learning cases even without any special prior knowledge. There were far more problems with instructional aspects of the production of cases. Most of these difficulties were very specific to the content of the cases. Therefore, it seems that an appropriate way to design learning cases with high quality, is a cooperation between some authors with different expertise. (shrink)

Mankind’s research on marketing has a history of hundreds of years, and it has been fruitful in continuous summary and research. Now the theory of marketing has gradually penetrated into the minds of every company and even individual. A successful marketing strategy is the inevitable result of scientific planning and effective implementation. However, the current marketing strategy has gradually failed to meet the needs of corporates. In order to find the best solution for corporate marketing strategy, we built a simulation (...) environment based on mobile computing and machine learning and compared the differences by simulating several companies of the same size in this city. The results of the study found that intelligent marketing based on machine learning is more suitable for enterprises than general marketing strategies. The efficiency of enterprises has increased by about 20%, and the income of enterprises has increased by more than 30% compared with traditional marketing strategies. This shows that the intelligent marketing strategy based on mobile computing and machine learning to build a simulated environment plays an extremely important role in the peculiarities. (shrink)

Under the wave of globalization, the ties between countries are getting closer and closer. Based on the differences in the languages of different countries, the importance of English as a universal language is becoming more and more prominent. In the past, English teaching was mainly taught by teachers and students. This mode of English learning is more of theoretical teaching, which has little effect on improving English ability. In the era of intelligence, with the upgrading of technology and the (...) renewal of ideas, interactive English teaching is more accepted by people and becomes a new solution for English teaching. Studying English teaching from the perspective of social cognition, this paper proposes to realize human-computer interaction with the help of advanced science and technology, create an interactive teaching environment, and realize interactive learning in an English environment. This paper designed a control experiment of the experimental group and the control group to verify the impact of human-computer interaction teaching on students’ English performance and investigated students’ performance and teachers’ feelings and their related opinions on human-computer interaction learning. The experimental results of this paper show that human-computer interactive English teaching can help to enhance students’ interest in English learning and improve English expression significantly. (shrink)

This study presents the evaluation of a computer-based learning program for children with developmental dyscalculia and focuses on factors affecting individual responsiveness. The adaptive training program Calcularis 2.0 has been developed according to current neuro-cognitive theory of numerical cognition. It aims to automatize number representations, supports the formation and access to the mental number line and trains arithmetic operations as well as arithmetic fact knowledge in expanding number ranges. Sixty-seven children with developmental dyscalculia from second to fifth grade (mean (...) age 8.96 years) were randomly assigned to one of two groups (Calcularis group, waiting control group). Training duration comprised a minimum of 42 training sessions à 20 minutes within a maximum period of 13 weeks. Compared to the waiting control group, children of the Calcularis group demonstrated a higher benefit in arithmetic operations and number line estimation. These improvements were shown to be stable after a 3-months post training interval. In addition, this study examines which predictors accounted for training improvements. Results indicate that this self-directed training was especially beneficial for children with low math anxiety scores and without an additional reading and/or spelling disorder. In conclusion, Calcularis 2.0 supports children with developmental dyscalculia to improve their arithmetical abilities and their mental number line representation. However, it is relevant to further adapt the setting to the individual circumstances. (shrink)

The paper introduces the concept of Computer-based Informated Environments (CBIEs) to indicate an emergent form of work organisation facilitated by information technology. It first addresses the problem of inconsistent meanings of the informate concept in the literature, and it then focuses on those cases which, it is believed, show conditions of plausible informated environments. Finally, the paper looks at those factors that when found together contribute to building a CBIE. It makes reference to CBIEs as workplaces that comprise (...) a non-technocentric perspective and questions whether CBIEs truly represent an anthropocentric route of information technology. (shrink)

Decision making often takes place in social environments where other actors influence individuals' decisions. The present article examines how advice affects individual learning. Five social learning models combining advice and individual learning‐four based on reinforcement learning and one on Bayesian learning‐and one individual learning model are tested against each other. In two experiments, some participants received good or bad advice prior to a repeated multioption choice task. Receivers of advice adhered to the advice, (...) so that good advice improved performance. The social learning models described the observed learning processes better than the individual learning model. Of the models tested, the best social learning model assumes that outcomes from recommended options are more positively evaluated than outcomes from nonrecommended options. This model correctly predicted that receivers first adhere to advice, then explore other options, and finally return to the recommended option. The model also predicted accurately that good advice has a stronger impact on learning than bad advice. One‐time advice can have a long‐lasting influence on learning by changing the subjective evaluation of outcomes of recommended options. (shrink)

Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment – Avida-ED – in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered.

This study examines the relationship between cognitive moral development (CMD), productivity features of information technology (IT) and unethical behavior or misconduct. Using an experimental design that randomly assigns subjects to one of four unique technology conditions, we assess the relationship between a subjects' predominant level of CMD and ethical misconduct on IT-oriented work tasks. Our results show that both higher levels of CMD and increased levels of IT productivity features at one's disposal have a significant role to play in explaining (...) observed behavior in our sample. We find that CMD as measured by the Defining Issues Test's P-score is negatively related to task misconduct. Conversely, IT productivity features such as copy-and-paste are positively related to task misconduct. In addition, the CMD—misconduct relationship is significantly diminished by the introduction of IT productivity features. Lastly, a series of hazard analyses are conducted to explore the boundaries of our principal findings. These results demonstrate the significant role of technology in enabling negative behavior and the relative inability of subjects' use of principled moral reasoning to overcome it. Implications of these findings for academics and business managers are offered, as well as recommendations for mitigating misconduct in both academic and workplace environments. (shrink)

Environmental landscaping is known to build, plan, and manage landscapes that consider the ecology of a site and produce gardens that benefit both people and the rest of the ecosystem. Landscaping and the environment are combined in landscape design planning to provide holistic answers to complex issues. Seeding native species and eradicating alien species are just a few ways humans influence the region’s ecosystem. Landscape architecture is the design of landscapes, urban areas, or gardens and their modification. It comprises the (...) construction of urban and rural landscapes via coordinating the creation and management of open spaces and economics, finding a job, and working within a confined project budget. There was a lot of discussion about global warming and water shortages. There is a lot of hope to be found even in the face of seemingly insurmountable obstacles. AI is becoming more significant in many urban landscape planning and design elements with the advent of web 4.0 and Human-Centred computing. It created a virtual reality-based landscape to create deep neural networks (DNNs) to make deep learning (DL) more user-friendly and efficient. Users may only manipulate physical items in this environment to manually construct neural networks. These setups are automatically converted into a model, and the real-time testing set is reported and aware of the DNN models that users are producing. This research presents a novel strategy for combining DL-DNN with landscape architecture, providing a long-term solution to the problem of environmental pollution. Carbon dioxide levels are constantly checked when green plants are in and around the house. Plants, on either hand, remove toxins from the air, making it easier to maintain a healthy environment. Human-centered Artificial Intelligence-based web 4.0 may be used to assess and evaluate the data model. The study findings can be sent back into the design process for further modification and optimization. (shrink)

Computer-based design environments for skilled domain workers have recently graduated from research prototypes to commercial products, supporting the learning of individual designers. Such systems do not, however, adequately support the collaborative nature of work or the evolution of knowledge within communities of practice. If innovation is to be supported within collaborative efforts, thesedomain-oriented design environments (DODEs) must be extended to becomecollaborative information environments (CIEs), capable of providing effective community memories for managing information and learning within (...) constantly evolving collaborative contexts. In particular, CIEs must provide functionality that facilitates the construction of new knowledge and the shared understanding necessary to use this knowledge effectively within communities of practice. (shrink)

Problem and Project Based Learning (PBL) has been used as an educational philosophy and methodology in the construction of a student centered and contextualized learning environment. PBL is also regarded as an effective method in producing engineering graduates who can not only meet the needs of professional competences but are also prepared for new challenges in the globalized and technological context. However, can PBL be a solution to the challenge of a general lack of university students studying engineering (...) and technology in many countries? Gender and Diversity in a Problem and Project Based Learning Environment presents an ethnographical study on the learning experiences of engineering students in the PBL environment in Denmark, and it attempts to question the issue of diversity in engineering education via the exploration of which ways the PBL environment is friendly to diverse groups of learners such as women. (shrink)

Basic Digital Education is already planned to be integrated with the forthcoming curriculum for Austrian primary schools as it was already implemented for lower secondary schools in 2018. BDE includes the most essential and novel developments of Computational Thinking, which are fundamentally responsible for nurturing students' problem-solving skills. Thus, evaluating teaching materials, scaffolding guidelines, and assessments is becoming increasingly important for the successful implementation of CT in Austrian classrooms. This study is a part of a longitudinal multi-cycle educational design research (...) project aiming to explore how to foster CT and to raise the awareness, importance, and confidence of teachers and students in applying CT for everyday uses. Our paper focuses on a sub-study in which teaching units for grade 3 and 4 students were designed by combining an Open Educational Resource textbook and Physical Computing with the micro:bit device. The designed learning environment consists of three units and was implemented in two classes over 3 weeks. The two classes were further split into two groups each, to ensure better support during implementation. The class teachers received upfront teacher training and conducted pre- and post-test assessments with the students. The resulting data was then analyzed to gain insights into the effects on CT skills of the young learners. Results showed that combining block-based programming and physical computing devices could become a promising approach to promote computational thinking skills in lower school grades. Furthermore, the observed direction of the designed units supports low-barrier access to increase the desired uses of CT in classrooms. (shrink)

This paper reviews computational models of surprise, with a specific focus on the authors’ probabilistic, contrast model. The contrast model casts surprise, and its intensity, as emerging from the difference between the probability of the surprising event and the probability of the highest expected‐event in a given situation. Strong arguments are made for the central role of surprise in creativity and learning by natural and artificial agents.

This research attempts to understand howchildren learn to use language. Instead ofusing syntax-based grammar rules to model thedifferences between children''s language andadult language, as has been done in the past, anew model is proposed. In the new researchmodel, children acquire language by listeningto the examples of speech that they hear intheir environment and subsequently use thespeech examples that have been previously heardin similar contextual situations. A computermodel is generated to simulate this new modelof language acquisition. The MALL computerprogram will listen (...) to examples of humanspeech, as would occur around a child, and thentry to use these examples in new situationsthat are similar to the contextual situationsin which the language examples were heard. This will provide a better understanding of howchildren learn to use language and howeducators can assist or improve the languagelearning process by providing required examplesof speech or by helping children to develop abetter understanding of similarities betweenvarious contexts. (shrink)

A teaching method may not work for all students. Therefore, attention should be paid to the type of students entering the learning environment in order to explain how they perceive the learning environment and achieve. This study investigates students? perceptions and achievement in four learning environments that differed in the degree to which case-based and lecture-based learning were implemented (either separately or combined), hereby making use of students? motivational and learning profiles. Participants were 1098 (...) first-year student teachers who took a course on child development. Results showed that autonomously motivated deep-strategic learners were significantly more positive about each type of learning environment than little motivated and less pronounced deep-strategic learners. However, with regard to achievement, student profiles did not differ. Instead, the learning environment proved to be of significant influence: students in a gradually implemented case-based setting and a completely lecture-based setting scored significantly higher than students in a completely case-based setting. (shrink)

This paper explores high school students' and teachers' preferences towards constructivist Internet‐based learning environments. The study proposes a framework, including two dimensions and five aspects, to illustrate the features of the Internet‐based learning environments. Based upon this framework, the Constructivist Internet‐based learning environment survey improvement was developed, which includes the scales of ease of use, multiple sources, student negotiation, reflective thinking, critical judgement and epistemological awareness. Questionnaire responses gathered from 630 high school students in Taiwan (...) suggested that the CILESI showed adequate reliability in assessing students' preferences. Male students placed more emphasis on the student negotiation, critical judgement and epistemological awareness enhanced by the Internet‐based learning environments than female students did. In addition, the teachers of the sampled students were also surveyed by CILESI. The teachers tended to express stronger preferences on the ease of use of the Internet‐based learning environments than did their students. However, students, when compared with their teachers, seemed to express more preferences towards the features of student negotiation, reflective thinking, critical judgement and epistemological awareness of Internet‐based learning environments. (shrink)

To what extent can external incentives influence students’ effort and learning in online course contexts? While cognitive science research has found that monetary incentives can increase goal-directed cognitive effort in certain laboratory tasks, attempts to use monetary incentives to increase students’ academic performance in naturalistic settings has shown mixed results. In two experiments, we tested the influence of a monetary incentive on immediate and delayed tests of computer-based educational performance. In Experiment 1, participants were assigned to receive monetary incentives (...) for correct quiz responses, or receive no additional incentive for correct responses other than finding out their score, and we found no significant difference in total score across groups. In Experiment 2, we used a within-subjects design to test whether participants performed better when they were provided monetary incentives for correct responses on quiz questions. Here, participants performed significantly better on incentivized quiz questions. Thus, monetary incentives may increase performance in online learning tasks when participants can anchor the “stakes” of an incentive compared to no external incentive. These findings highlight potential benefits of external incentives for promoting effort and learning in online contexts, although further research is needed to determine the most useful educationally-relevant extrinsic incentives, as well as potential negative effects of incentives on long-term intrinsic motivation. (shrink)

Salient landmarks enhance route learning. We hypothesised that semantically salient nostalgic landmarks would improve route learning compared to non-nostalgic landmarks. In two experiments, participants learned a route through a computer-generated maze using directional arrows and wall-mounted pictures. On the test trial, the arrows were removed, and participants completed the maze using only the pictures. In the nostalgia condition, pictures were of popular music artists and TV characters from 5 to 10 years ago. In the control condition, they were (...) recent pictures of these same artists and characters. In Experiment 1, in the test trial, participants in the nostalgia condition completed the maze faster than controls. Experiment 2 conceptually replicated these findings and extended them by exploring boundary conditions. Participants had to learn two mazes sequentially. In Maze 1, we placed nostalgic/control landmarks only at non-decision points (whereas we placed them at decision points in Experiment 1). In Maze 2, we placed nostalgic/control landmarks at decision points during acquisition but removed them in the test trial (whereas they were present in the test trial in Experiment 1). In both mazes, participants in the nostalgia (compared to control) condition completed the test trial faster. (shrink)

This paper is concerned with adaptive learning and coordination processes. Implementing agent-based modeling techniques (Learning Classifier Systems, LCS), we focus on the twofold impact of cognitive and environmental complexity on learning and coordination. Within this framework, we introduce the notion of Adaptive Learning Agent with Rule-based Memory (ALARM), which is a particular class of Artificial Adaptive Agent (AAA, Holland and Miller 1991). We show that equilibrium is approached to a high degree, but never perfectly reached. We (...) also demonstrate that memorization and learning capacities depend upon the relative discordance between the cognitive complexity of agents' mental models and the degree of stability of the environment. (shrink)

Implicit learning is a core process for the acquisition of a complex, rule‐based environment from mere interaction, such as motor action, skill acquisition, or language. A body of evidence suggests that implicit knowledge governs music acquisition and perception in nonmusicians and musicians, and that both expert and nonexpert participants acquire complex melodic, harmonic, and other features from mere exposure. While current findings and computational modeling largely support the learning of chunks, some results indicate learning of more complex (...) structures. Despite the body of evidence, more research is required to support the cross‐cultural validity of implicit learning and to show that core and more complex music theoretical features are acquired implicitly. (shrink)

Providing an inclusive and quality education for all contributes toward the Sustainable Development Goals of the United Nations. High-quality learning environments based on what works in education benefit all students and can be particularly beneficial for children with disabilities. This article contributes to advance knowledge to enhance the quality of education of students with disabilities that are educated in special schools. This research analyses in which ways, if any, interactive learning environments can be developed in special (...) schools and create better learning opportunities for children with disabilities. A case study was conducted with students with disabilities (N = 36) and teaching staff in a special school, involving interviews and focus groups. We argue that rethinking the learning context by introducing instruction models based on interaction benefit children with disabilities and provide high-quality learning and safe and supportive relationships for these students, thereby promoting their educational and social inclusion. (shrink)

In recent years, several Vygotskian computer-based learning activities (VCBLAs) were designed in the context of (mathematics) education and implemented on Moodle platform. However, Moodle does not allow users to visualize all chats on a single browser page, and they are forced to open multiple browser windows and switch among them very frequently. This paper describes the features of a plugin for Moodle, called “Quick Chat,” which allows to manage in a single browser window both the narrative flow of a (...) VCBLA and all chats. Some results of an experimentation with PhD students, engaged in solving two mathematical tasks, are shown. (shrink)

This work focuses on the application of machine learning techniques to assist the clinicians in the administration of analgesic drug during general anaesthesia. Specifically, the main objective is to propose the basis of an intelligent system capable of making decisions to guide the opioid dose changes based on a new nociception monitor, the analgesia nociception index. Clinical data were obtained from 15 patients undergoing cholecystectomy surgery. By means of an off-line study, machine learning techniques were applied to analyse (...) the possible relationship between the analgesic dose changes performed by the physician due to the hemodynamic activity of the patients and the evolution of the ANI. After training different classifiers and testing the results under cross validation, a preliminary relationship between the evolution of ANI and the dosage of remifentanil was found. These results evidence the potential of the ANI as a promising index to guide the infusion of analgesia. (shrink)

In the international context of a progress toward more inclusive educational systems and practices, the role of Special Education teachers is being transformed. From an inclusive perspective, these professionals increasingly support students and their teachers in the mainstream classroom, avoiding segregation. However, Special Education teachers often struggle to reach and support all students with special needs and their teachers to provide quality inclusive education. For this reason, more research is still needed on in-service training strategies for the inclusion of students (...) with special needs that effectively translate into evidence-based school practices that improve the education of all students. This article analyses the impact of two evidence-based dialogic training programs of Special Education teachers working in mainstream schools carried out in Mexico during the 2018–2019 school year. Through in-depth interviews with participants, it was identified how, after the training, teachers increasingly grounded their actions on scientific evidence and promoted interactive learning environments that improved the educational inclusion of their students with special needs. This training also became the venue to make evidence-based educational actions available to other students without special needs, improving the quality of education provided to all students. (shrink)

This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision‐making process: instance‐based knowledge, recognition‐based retrieval, adaptive strategies, necessity‐based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refinement of instances, containing the decision‐making situation, action, and utility of decisions. As decision makers interact with a dynamic task, they recognize a situation according to its similarity (...) to past instances, adapt their judgment strategies from heuristic‐based to instance‐based, and refine the accumulated knowledge according to feedback on the result of their actions. The IBLT's learning mechanisms have been implemented in an ACT‐R cognitive model. Through a series of experiments, this paper shows how the IBLT's learning mechanisms closely approximate the relative trend magnitude and performance of human data. Although the cognitive model is bounded within the context of a dynamic task, the IBLT is a general theory of decision making applicable to other dynamic environments. (shrink)

In this research work, a user-friendly decision support framework is developed to analyze the behavior of Pakistani students in academics. The purpose of this article is to analyze the performance of the Pakistani students using an intelligent decision support system (DSS) based on the three-level machine learning (ML) technique. The neural network used a three-level classifier approach for the prediction of Pakistani student achievement. A self-recorded dataset of 1,011 respondents of graduate students of English and Physics courses are used. (...) The ten interviews along with ten questions were conducted to determine the perception of the individual student. The chi-squared ( χ ) \left(\chi ) test was applied to test statistical significancy of the questionnaire. The statistical calculations and computation of data were performed by using the statistical package of IBMM SPSS version 21.0. The seven different algorithms were tested to improve the data classification. The Java-based environment was used for the development of numerous prediction classifiers. C4.5 algorithm shows the finest accuracy, whereas Naïve Bayes (NB) algorithm shows the least. The results depict that the classifier’s efficiency was improved by using a three-level proposed scheme from 83.2% to 88.8%. This prediction has shown remarkable results when compared with the individual level classifier technique of ML. This improvement in the accuracy of DSSs is used to identify more efficiently the gray areas in the education stratum of Pakistan. This will pave a path for making policies in the higher education system of Pakistan. The presented framework can be deployed on different platforms under numerous operating systems. (shrink)

Nursing education is in the process of incorporating critical thinking, social justice, and health inequality perspectives into educational structures, aspiring to help nursing students develop into professional nurses prepared to provide equal care. Norm criticism is a pedagogical philosophy that promotes social justice. This qualitative case study aimed to gain an understanding of and elaborate on an educational development initiative in which norm criticism was incorporated into the composition of a new campus‐based clinical learning environment for nursing education. By (...) analyzing documents and interviews with the help of reflexive thematic analysis three themes were generated: “Intention to educate beyond nursing education,” “Educating in alliance with society,” and “The educative ambiguity of the Clinical Learning Centre.” The case study indicates that the incorporation of norm criticism into a campus‐based clinical learning environment may encourage nursing students to evolve social skills for nursing practice that support health equality within healthcare. By collaborating with society, nursing education can considerably improve its educational frameworks in alignment with societal demands. However, the inclusion of norm criticism in a setting such as a campus‐based clinical learning environment entails a clash with established institutionalized norms and being perceived as too proximate to politics. (shrink)

Because of the difficulty of music feature recognition due to the complex and varied music theory knowledge influenced by music specialization, we designed a music feature recognition system based on Internet of Things technology. The physical sensing layer of the system places sound sensors at different locations to collect the original music signals and uses a digital signal processor to carry out music signal analysis and processing. The network transmission layer transmits the completed music signals to the music signal database (...) in the application layer of the system. The music feature analysis module of the application layer uses a dynamic time regularization algorithm to obtain the maximum similarity between the test template and the reference. The music feature analysis module of the application layer uses the dynamic time regularization algorithm to obtain the maximum similarity between the test template and the reference template to realize the feature recognition of the music signal and determine the music pattern and music emotion corresponding to the music feature content according to the recognition result. The experimental results show that the system operates stably, can capture high-quality music signals, and can correctly identify music style features and emotion features. The results of this study can meet the needs of composers’ assisted creation and music researchers’ analysis of a large amount of music data, and the results can be further transferred to deep music learning research, human-computer interaction music creation, application-based music creation, and other fields for expansion. (shrink)

Objective We conducted a process evaluation to (a) assess the effectiveness of a new problem-based learning curriculum designed to teach professionalism and scientific integrity to biomedical graduate students and (b) modify the course to enhance its relevance and effectiveness. The content presented realistic cases and issues in the practice of science, to promote skill development and to acculturate students to professional norms of science. Method We used 5-step Likert-scaled questions, open-ended questions, and interviews of students and facilitators to assess (...) curricular effectiveness. Results Both facilitators and students perceived course objectives were achieved. For example, respondents preferred active learning over lectures; both faculty and students perceived that the curriculum increased their understanding of norms, role obligations and responsibilities of professional scientists. They also reported an increased ability to identify ethical situations and felt that they had developed skills in moral reasoning and effective group work. Conclusions These data helped to improve course implementation and instructional material. For example, to correct a negative perception that this was an ‘ethics’ course, we redesigned case debriefing activities to reinforce learning objectives and important skills. We refined cases to be more engaging and relevant for students, and gave facilitators more specific training and resources for each case. The problem-based learning small group strategy can stimulate an environment whereby participants are more aware of ethical implications of science, and increase their socialisation and open communication about professional behaviour. (shrink)

Argument-mapping software abounds, and one of the reasons is that using the software has been shown to teach/promote/improve critical thinking skills. These positive results are very encouraging, but they also raise the question of whether the computer tutorial environment is producing these results, or whether learning argument mapping, even with just paper and pencil, is sufficient. Based on the results of two empirical studies, I argue that the basic skill of being able to represent an argument diagrammatically plays an (...) important role in the improvement of critical-thinking skills. While these studies do not offer a direct comparison between the two methods, it is important for anyone wishing to employ argument mapping in the classroom to know that significant results can be obtained even with the most rudimentary of tools. (shrink)

Prior knowledge structures (or schemas) confer multiple behavioral benefits. First, when we encounter information that fits with prior knowledge structures, this information is generally better learned and remembered. Second, prior knowledge can support prospective planning. In humans, memory enhancements related to prior knowledge have been suggested to be supported, in part, by computations in prefrontal and medial temporal lobe cortex. Moreover, animal studies further implicate a role for the hippocampus in schema-based facilitation and in the emergence of prospective planning signals (...) following new learning. To date, convergence across the schema-enhanced learning and memory literature may be constrained by the predominant use of hippocampally dependent spatial navigation paradigms in rodents, and non-spatial list-based learning paradigms in humans. Here, we targeted this missing link by examining the effects of prior knowledge on human navigational learning in a hippocampally dependent virtual navigation paradigm that closely relates to foundational studies in rodents. Outside the scanner, participants overlearned Old Paired Associates (OPA – item-location associations) in multiple spatial environments, and they subsequently learned New Paired Associates (NPA – new item-location associations) in the environments while undergoing fMRI. We hypothesized that greater OPA knowledge precision would positively affect NPA learning, and that the hippocampus would be instrumental in translating this new learning into prospective planning of navigational paths to NPA locations. Behavioral results revealed that OPA knowledge predicted one-shot learning of NPA locations, and neural results indicated that one-shot learning was predicted by the rapid emergence of performance-predictive prospective planning signals in hippocampus. Prospective memory relationships were not significant in parahippocampal cortex and were marginally dissociable from the primary hippocampal effect. Collectively, these results extend understanding of how schemas impact learning and performance, showing that the precision of prior spatial knowledge is important for future learning in humans, and that the hippocampus is involved in translating this knowledge into new goal-directed behaviors. (shrink)

The twenty-first century is arguably the century of computing. In such a world saturated by computing, Computational Thinking is now recognized as a foundational competency for being an informed citizen and being successful in STEM work. Nevertheless, how to effectively import different types of teaching methods in university courses is subjected to further evaluation. Currently, the arguments in favor of tangible robots including high interaction, great practicality, and specific operation results make themselves to be often used as a teaching medium (...) and tool for teaching activities between teachers and students. Hence, in addition to cultivating students with computational thinking ability, this paper discussed how to integrate tangible robots into project-based learning courses of thinking skills training to improve the learning performance of the computational thinking ability. This study conducted in one semester on the 105 students from three classes. Experimental results show that the project-based learning method integrated with the teaching material of robotic visual programs approach had significantly better effectiveness in improving students' learning achievements than the traditional teaching method integrated with paper practice teaching materials approach. Analysis of the questionnaire results showed that the proposed learning approach did not increase the students' cognitive burden. In sum, the proposed approach helps students' learning achievement and cognitive load. (shrink)

Artificial intelligence technology has been widely applied in many fields. AI-assisted learning environments have been implemented in classrooms to facilitate the innovation of pedagogical models. However, college students' willingness to accept AI-assisted learning environments has been ignored. Exploring the factors that influence college students' willingness to use AI can promote AI technology application in higher education. Based on the Unified Theory of Acceptance and Use of Technology and the theory of perceived risk, this study identified six (...) factors that influence students' willingness to use AI to analyze their relationships with WTA AI-assisted learning environments. A model including six hypotheses was constructed to test the factors affecting students' WTA. The results indicated that college students showed “weak rejection” of the construction of AI-assisted learning environments. Effort expectancy, performance expectancy, and social influence were all positively related to college students' WTA AI-assisted learning environments. Psychological risk significantly negatively influenced students' WTA. The findings of this study will be helpful for carrying out risk communication, which can promote the construction of AI-assisted learning environments. (shrink)

Violence suffered by children is a violation of human rights and a global health problem. Children with disabilities are especially vulnerable to violence in the school environment, which has a negative impact on their well-being and health. Students with disabilities educated in special schools have, in addition, more reduced experiences of interaction that may reduce both their opportunities for learning and for building protective social networks of support. This study analyses the transference of evidence-based actions to prevent violence in (...) schools – the dialogic model of prevention and resolution of conflicts (DMPRC) – in the context of a special school, and its impact on the reduction of violence, the creation of egalitarian relationships, and the prevention of bullying. A case study with a communicative approach was conducted including in-depth interviews and communicative focus groups with the diverse participants to analyze the process of transformation carried out in the school and the main actions that give students a voice in the management and creation of egalitarian non-violent relationships. The results show that the inclusion of the students’ voices in the resolution and prevention of conflicts reduces violence, empowers special education students, strengthens friendship relationships, caring behavior, and active positioning among the community. The positive impact of the transference of the DMPRC to special schools contributes to students’ well-being and healthy development by offering safe and protective educational spaces and quality emotional education, also contributing to the achievement of the Sustainable Development Goals related to the elimination of all forms of violence in childhood. (shrink)

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely (...) different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. (shrink)

Dementia, a prevalent disorder of the brain, has negative effects on individuals and society. This paper concerns using Spontaneous Speech Challenge of Interspeech 2020 to classify Alzheimer's dementia. We used VGGish, a deep, pretrained, Tensorflow model as an audio feature extractor, and Scikit-learn classifiers to detect signs of dementia in speech. Three classifiers were 59.1% accurate, which was 3% above the best-performing baseline models trained on the acoustic features used in the challenge. We also proposed DemCNN, a new PyTorch raw (...) waveform-based convolutional neural network model that was 63.6% accurate, 7% more accurate then the best-performing baseline linear discriminant analysis model. We discovered that audio transfer learning with a pretrained VGGish feature extractor performs better than the baseline approach using automatically extracted acoustic features. Our DepCNN exhibits good generalization capabilities. Both methods presented in this paper offer progress toward new, innovative, and more effective computer-based screening of dementia through spontaneous speech. (shrink)

In response to concern over the numeracy skills deficit displayed by student nurses, an online computer programme, ?Authentic World??, which aims to simulate a real-life clinical environment and improve the medication dosage calculation skills of users, was developed (Founded in 2004 Authentic World Ltd is a spin out company of Glarmorgan and Cardiff Universities, Cardiff, Wales UK.). Two randomised controlled trials were conducted, each at a UK University, in order to investigate the impact of Authentic World? on student nurses? general (...) numeracy abilities. All first year nursing students who gave consent were randomised equally into an intervention or control group. The intervention group were given access to Authentic World?. The primary outcome measure was the students? scores on a general numeracy test. The Intention to Treat (ITT) analysis in both trials revealed a small negative effect of Authentic World? on general numeracy, which was statistically significant in one trial. However, compliance with the intervention was very low in both trials, with only 24 and 12% of students allocated to the intervention groups spending more than 15 minutes using the programme. Providing nursing students with access to Authentic World? is not an effective use of resources since use of the programme appears to be very low. (shrink)

Growing evidence in recent years has led to an agreement on the importance and benefits that inclusive education has for students with special educational needs (SEN). However, the extension and universalization of an inclusive approach will also be enhanced with more evidence on the benefits that inclusion has for all students, including those without SEN. Based on the existing knowledge that learning interactions among diverse students are a key component of educational inclusion, the aim of this study is to (...) identify the impact on students without SEN of being educated with students with SEN in shared, inclusive, interactive learning environments. Data were collected in three schools using a qualitative approach with a communicative orientation. Semistructured interviews were held with teachers as well as community volunteers participating in the schools. Further, focus groups were conducted with students and teachers. The results show that students without SEN benefit from participating in interactive learning activities with peers with SEN in different ways: (1) they learn to respect others, accept differences, and acknowledge different abilities, thereby creating opportunities for new friendships to develop; (2) they learn about abilities related to helping others participate and learn, to be patient and to gain the satisfaction in helping others learn and behave better; and (3) they benefit from the cognitive effort required to explain themselves and from the contributions of peers with SEN from which they can learn. (shrink)

To be relevant to the constantly changing work patterns of the real world, effective learning in universities often occurs in small groups facilitated by collaborative environments where participants are dynamically involved in purposeful activities. The research described in this paper is an investigation of purposeful group work devised for experiential learning where a variety of socio-technical tools were used to support asynchronous tasks and communication among the learners. In order to explore the complexity of this collaborative activity (...) a distinctive inductive research approach has been adopted using reflective developmental methods. The data collection and the analysis part of the research involved the reflection of participants on their activity being requested as reports within their course work. Student reports were subject to content analysis using a computer-based tool that creates a conceptual map of collections of documents comparing the ratings and relationships of concepts among different sets of participants. The study was enhanced by the use of Q-methodology that allows the participants to outline their views and to make individual decisions on the relative importance that they place upon the available views of the larger group. Concepts from Activity Theory allowed the researchers to take a holistic contextual approach both to the design of the research and the interpretation of the findings to make some sense of the complexity of the dynamic work-learning dialectic in a socio-technical collaborative setting. (shrink)

The paper discusses tools for teaching logic used in Logic & Proofs, a web-based introduction to modern logic that has been taken by more than 1,300 students since the fall of 2003. The tools include a wide array of interactive learning environments or cognitive mini-tutors; most important among them is the Carnegie Proof Lab. The Proof Lab is a sophisticated interface for constructing natural deduction proofs and is central, as strategically guided discovery of proofs is the distinctive focus (...) of the course. My discussion makes explicit the broader intellectual context, but also the pursuit of pedagogical goals and their experimental examination. The intellectual context includes i) the theoretical background for the proof search algorithm AProS and its use for a dynamic Proof Tutor, and ii) the programmatic expansion of the course to Computational Logic. 1. (shrink)

A sector is a basic unit of airspace whose operation is managed by air traffic controllers. The operation complexity of a sector plays an important role in air traffic management system, such as airspace reconfiguration, air traffic flow management, and allocation of air traffic controller resources. Therefore, accurate evaluation of the sector operation complexity is crucial. Considering there are numerous factors that can influence SOC, researchers have proposed several machine learning methods recently to evaluate SOC by mining the relationship (...) between factors and complexity. However, existing studies rely on hand-crafted factors, which are computationally difficult, specialized background required, and may limit the evaluation performance of the model. To overcome these problems, this paper for the first time proposes an end-to-end SOC learning framework based on deep convolutional neural network specifically for free of hand-crafted factors environment. A new data representation, i.e., multichannel traffic scenario image, is proposed to represent the overall air traffic scenario. A MTSI is generated by splitting the airspace into a two-dimension grid map and filled with navigation information. Motivated by the applications of deep learning network, the specific CNN model is introduced to automatically extract high-level traffic features from MTSIs and learn the SOC pattern. Thus, the model input is determined by combining multiple image channels composed of air traffic information, which are used to describe the traffic scenario. The model output is SOC levels for the target sector. The experimental results using a real dataset from the Guangzhou airspace sector in China show that our model can effectively extract traffic complexity information from MTSIs and achieve promising performance than traditional machine learning methods. In practice, our work can be flexibly and conveniently applied to SOC evaluation without the additional calculation of hand-crafted factors. (shrink)