Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Motivation: Theory And Research

Abstract Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students’ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness. 

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Interacting with educational chatbots: A systematic review

Spanish Abstract: Este articulo describe el sistema tributario chileno y analiza el contexto politico que impidio reformas que transformaran el regresivo sistema establecido durante el regimen dictatorial. Examina el proceso de formulacion de politicas tributarias despues de la democratizacion y las estrategias que emplearon los gobiernos de la coalicion de centro izquierda para lograr la aprobacion de reformas incrementales. Por ultimo, muestra que el ambiente politico cambio luego de las protestas estudiantes de 2011 y 2012, lo que hizo posible la aprobacion de la reforma tributaria mucho mas progresiva propuesta por la presidente Bachelet en 2014.English Abstract: This article describes the Chilean tax system and analyzes the political context prevented regressive reforms to transform the system established during the dictatorship. Examines the formulation of tax policy after democratization and the strategies employed by the governments of the center-left coalition for the passage of incremental reforms. Finally, it shows that the political atmosphere changed after the student protests of 2011 and 2012, which made possible the adoption of more progressive tax reform proposed by President Bachelet in 2014.

La Economía Política De La Reforma Tributaria Progresiva En Chile (The Political Economy of Progressive Tax Reform in Chile)

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Mentoring Model in an Active Learning Culture for Undergraduate Projects

Article history: Received: 30 August, 2020 Accepted: 01 November, 2020 Online: 20 November, 2020 Teaching tax-related regulations have always been a challenge due to the inclusion of external variables that hinder the learning process, such as the high complexity of tax systems and legislation variability. Universities have sought different alternatives to support the teaching process both outside and inside the classroom, ranging from recreational activities to active learning. This article will show the experience resulting from using a chatbot to support learning in accounting students for the teaching of tax regulations related to the Chilean tax system, comparing two types of tools, on the one hand, a free conversation chatbot using natural language processing versus a rule-based chatbot driven by a decision tree. The experimentation process was carried out with 50 higher education students, divided into an experimental group and a control group, in two different courses. The results obtained demonstrated in both cases greater effectiveness of the use of the chatbot in learning the tax matter, both in the free conversation chatbot where the experimental group obtained a 15.7% improvement versus the control group that obtained a 1.05% improvement, as in the chatbot that applied decision tree where the experimental group obtained a 32% improvement versus the control group with 5.2%. Considering the complexity of the content in tax matters and the little innovation in the existing teaching subjects in the area and that the students improve learning using both chatbot tools compared to other learning techniques, is considered a relevant contribution to teaching innovation.

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María Blanco-Lobos

Papers

Effective Learning of Tax Regulations using Different Chatbot Techniques