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... Q i Test questions, C x Tested concepts, L k Bloom link of level k, VS(k) Verified skills at level K and (Q i ,C x )L k means existing link between the question Q i and the concept C x at level K. The link means that to answer Q i correctly C x must be learned at level k. Fig. 3 shows verified skill link. ...
Context 2
... between the questions and the concepts, e.g., Qi is a question asked for the concept Cx. The relation is such that to answer the Question Qi. correctly, the Student Si should know the concept Cx at level Lk. The link then could be connected to CLMCG and the link is denoted as (Qi,Cx)Lk. This link represent the concept state VS as illustrated in Fig. 3. Likewise, all the required concepts to answer Qi will be connected to the question Qi. In the next paragraph, we introduce the estimation methods of the three sets of concept state VS, DS, and PS and how they could be linked with CLMCG. First step is to connect the question with CLMCG. A test normally is composed of a set of ...
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Testing is a well-established desirable difficulty. Yet there are still some open issues regarding the benefits of testing that need to be addressed. First, the possibility to increase its benefits by adapting the sequence of test questions to the learners’ level of knowledge has scarcely been explored. In view of theories that emphasize the benefi...
Engaging students in a challenging (cognitively demanding) task and launching a mathematics lesson with a task before instruction are two characteristics of a reform-oriented approach to mathematics instruction often considered together. The authors systematically contrasted teaching with challenging tasks using a task-first lesson structure with t...
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... These applications and tools are also promoted as facilitating HOTS in blended learning settings. There is, however, a scarcity of research exploring how such smart classroom teaching strategies are applied for demonstrable enhancement of students' HOTS [23,32,33]. Some attempts have been made in specific subject topics within a restricted environment that has resulted in siloed effects [34,35]. ...
The development of Industry 4.0 revolutionising the concept of automation and digitisation in an organisation poses a huge challenge in employee knowledge and skills to cope with the huge leap from Industry 3.0. The high-level digitisation of an organisation requires the workforce to possess higher order thinking skills (HOTS) for the changing job roles matching the rapid technological advancements. The Education 4.0 framework is aimed at supporting the Industry 4.0 skills requirement not only in digital technologies but more towards soft skill development such as collaboration and lifelong learning. However, the education sector is also facing challenges in its transition from Education 3.0 to Education 4.0. The main purpose of the paper is to propose an Agile approach for developing smart classroom teaching strategies that foster employee adaptability with the new learning paradigm of upskilling in line with Industry 4.0. By adopting an exploratory research methodology, the pilot study investigates the implementation of the proposed Agile approach in a higher education setting for graduates to achieve HOTS using smart classroom teaching strategies. This study uses learning theories such as experiential learning in smart classroom environments to enhance students’ HOTS individually as well as collaboratively in an Agile iterative manner. This is the first empirical study carried out for graduates specialising in the Business Analytics skillset required for Industry 4.0. The findings of the pilot study show promising results that pave the way for further exploration and pedagogical insights in this research direction.
... Based on the previous research, a person's cognitive skills refer to their ability to apply and analyze newly acquired knowledge (Aboalela & Khan, 2016). As a result, the cognitive abilities of children with intellectual disabilities are still being assessed, as learning requires an assessment to determine progress in understanding and application. ...
... Assessment is an important part of the learning process (Aboalela & Khan, 2016;Mustafa & Masgumelar, 2022). Assessment of adaptive physical education from the cognitive aspect is a benchmark carried out by teachers for their students which aims to determine students' knowledge abilities. ...
Adaptive physical education is a type of physical education geared toward children with special needs, such as intellectual disabilities. Of course, there must be an assessment in learning to see if the results taught from the cognitive, affective, and psychomotor perspectives were achieved. The goal of this research was to learn more about how physical education learning outcomes were assessed in schools for students with intellectual disabilities in Semarang. The research method used was descriptive. This method aims to describe the events and circumstances that occurred. The research approach used was qualitative. Data were gathered through observation, interviews, and documentation. The informant for this study was a Semarang-based special school teacher (SLB) who teaches physical education classes. The findings revealed that teachers had difficulty making assessments for mentally retarded students even though the assessment was still conducted as it should. It was determined that the teacher conducted a cognitive, affective, and psychomotor assessment of physical education learning and modified the assessment indicators to find appropriate standards. Meanwhile, the assessment was carried out based on the students' abilities.
... Vale ressaltar que os alunos foram separados em grupos, cuja escolha dos integrantes foi realizada por afinidade entre eles, não havendo, assim, interferências por parte da professora responsável pela turma (puppetmaster do jogo). Cada grupo foi identificado por cores e o jogo teve duração de 7 dias (168 horas), conforme pode ser visto na Figura 2. Vale destacar que cada uma das fases possuía complexidades diferentes e mobilizava vários níveis de habilidades cognitivas necessários para a resolução dos problemas e execução das tarefas, tais como: nível de compreensão, aplicação, análise, avaliação ou criação (Aboalela & Khan, 2016). Os enigmas inseridos no jogo na forma de problemas concentraram-se na mesma área dos conteúdos químicos utilizados para compor a narrativa do ARG e estavam embasados e estruturados para abarcar os três níveis representacionais do conhecimento químico (submicroscópico, macroscópico e representacional). ...
O ensino de química vem passando por tentativas de repaginação. Nesse sentido, várias estratégias estão surgindo ou sendo adaptadas para torná-lo mais efetivo para a aprendizagem dos alunos, ao fortalecer competências de pensamento crítico, de comunicação e de colaboração, além do letramento tecnológico. Este artigo aponta para mudanças e inovações, pois discutimos o uso de um Jogo de Realidade Alternativa (ARG) como estratégia avaliativa no ensino de química. Este tipo de jogo consiste em uma narrativa interativa ambientada no mundo real. A pesquisa apresentada é de natureza qualitativa e foi realizada com 35 discentes (n=35) de um curso de formação inicial em ensino de ciências. Os dados foram analisados sistematicamente e categorizados. Os resultados mostram que o ARG influenciou positivamente a colaboração entre os pares e aumentou a capacidade dos alunos em resolver desafios abarcando diferentes níveis de representação do conhecimento químico. O estudo mostra evidências de que o ARG pode ser utilizado como estratégia de avaliação de aprendizagem de natureza formativa, diagnóstica e autoavaliativa. Por fim, apresentamos um modelo avaliativo utilizando o ARG que pode ser aplicado em diferentes níveis de aprendizagem da química.
... [8] visualized the concept space of course content by three dimensions: Syllabus, Ontological and Cognitive dimension. Moreover, the research work of [9,10] validate the efficiency and the importance of using the parameter of conative skill level to assess the knowledge in one domain. ...
... In this study, the researchers concentrate on the concepts as they appear in the text in either phrase form or single word form and identify the link between the concepts, as the skill required to learn the concept at a certain skill level, which identifies the prerequisite relation between the concepts. Moreover, [5], [6] studied and validated the efficiency and importance using the parameter of cognitive skill level to assess the knowledge in one domain. The research work [7] introduce a model of the cognitive level relation between the concepts in the learning assessment. ...
In these research zones of the knowledge, the assessed domain is identified. Explicitly, these zones are known as Verified Skills, Derived Skills and Potential Skills. In detail, the Verified Skills Zone is the set of tested concepts in the knowledge domain, while Derived Skills Zone is the set of the prerequisite concepts to the tested concepts based on the cognitive skills relation, whereas Potential Skills Zone is the set in the domain that have never been tested or prerequisite to the tested concepts but they are related to the tested concept based on the cognitive relation skills. Identifying cognitive relations between the concepts in one domain simplifies the structure of the assessment, which helps to find the knowledge state of the assessed individual in a short time and minimum number of questions. The existence of the concepts in the assessment domain helps us to estimate the set of the concepts that are known or not known or ready to be known or not ready to be known. In addition, it provides the output of the assessment in concept centric values in addition to the quantity values. The assessment result gives binary values of the assessed domain. "1" implies knowing the concept, whereas "0" implies not knowing the concept. The output is six sets of concepts: 1) Verified Known Skills; 2) Verified Not Known Skills; 3) Derived Known Skills; 4) Derived Not Known Skills; 5) Potential Known Skills; and 6) Potential Not Known Skills. The experiment is conducted to show the binary output of the assessed domain based on the participants' answers to the asked questions. The results also highlight the efficiency of the assessment.
Almost sixty years after Scriven and Bloom’s accurate description and differentiation between summative and formative assessment, it would be quite vain to make sure that educators nowadays fully understand and use these two types of evaluation in their practice. Besides, it would be riskier to expect educators to use programs or design AI algorithms to make appropriate decisions to select and design instruments to make accurate judgments about learning and performance results without considering the difficulties in learning evaluation practices that have arisen in different educational contexts. The understanding of paradigms, educational models, and beliefs of educators around assessment practices constitutes mandatory tasks to consider as a point of departure in the era of ICT for learning purposes. Thus, the main objective of this chapter is to review the importance of evaluation literacy towards the complex challenge of planning, designing instruments, and interpreting results derived from learning assessment. Then, a reflection on the advances and difficulties found by researchers in different countries on formative and summative practices and results in higher education mainly is discussed. By the end of this chapter, some recommendations related to educator's training for improving and reinforcing conceptual and instrumental assessment practices are envisaged.
Performance of learning can be enriched with proper and timely feedback. This paper proposes a solution based on a Bayesian network in machine learning that can examine and judge students’ written response to identify evidences that students fully comprehend concepts being considered in a certain knowledge domain. In particular, it can estimate probabilities that a student has known concepts in computer science at different cognitive ability levels in a sense. Thus, the method can offer learners personalized feedbacks on their strengths and shortcomings, as well as advising them and instructors of supplementary education actions that may help students to resolve any lacks to improve their knowledge and exam score.
É um consenso na literatura de que o uso do lúdico em sala de aula permite a promoção de uma aprendizagem ativa, desenvolve habilidades mentais de diferentes níveis, facilita a participação de alunos com diferentes estilos de aprendizagem, incentiva o ensino entre pares e a aprendizagem colaborativa. Diante dessas contribuições, consideramos que podemos usar abordagens lúdicas para outras atividades, além da sala de aula. Assim, neste artigo, temos como objetivo relatar a experiência de utilização de um jogo de trilha (denominado TAG) em uma tentativa de gamificar o momento de apresentação oral de trabalhos no JALEQUIM Level III, realizado na Universidade da Integração Latino-Americana. Nos resultados, além de apresentar o processo de concepção e produção do jogo, coletamos relatos de três coordenadores de sessão, a fim de, a partir de suas experiências, analisarmos a receptividade e contribuição da proposta. Assim, constamos as contribuições e limitações da utilização da TAG no referido evento.
We describe a machine-learning system for supporting teachers through the selection of homework assignments. Our system uses behavioural cloning of teacher activity to generate personalised homework assignments for students. Classroom use is then supported through additional mechanisms to combine these predictions into group assignments. We train and evaluate our system against 50,065 homework assignments collected over two years by the Isaac Physics platform. We use baseline policies incorporating expert curriculum knowledge for evaluation and find that our technique improves on the strongest baseline policy by 18.5% in Year 1 and by 13.3% in Year 2.
