Instructional Design: International Perspectives

Dijkstra, S.; Schott, Franz; Tennyson, Robert D.; Seel, Norbert M.

doi:10.4324/9780203052778

Cited by 4 publications

(1 citation statement)

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“…An on-going debate within the instructional design community about which of these aspects of design (creativity or engineering) are most prominent and relevant to instructional planning and implementation is now in action [7]. The view herein is that instructional design principles, rules, guidelines and heuristics do exist, although they are sensitive to local conditions(learners, instructional setting, support resources, learning cultures, and so on).…”

Section: Competencesmentioning

confidence: 98%

Instructional Design Oriented Towards the Development of Competences

Giraldo

Acuna²

2005 6th International Conference on Information Technology Based Higher Education and Training

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This article presents instructional design oriented towards the development of competences. First, the competence concept is developed showing its pertinence in the business as well as in the academic field. In the second part, we develop the definition, properties, evolution and components of the instructional design. In the third part, competences and instructional design are integrated and a methodology with basic aspects of design and strategies oriented to the development of competences is proposed. Finally, we present a series of guidelines for applying this model in the development of courses.

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Section: Competencesmentioning

confidence: 98%

Instructional Design Oriented Towards the Development of Competences

Giraldo

Acuna²

2005 6th International Conference on Information Technology Based Higher Education and Training

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Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding

Clayton

Abbass

2019

2019 IEEE Congress on Evolutionary Computation (CEC)

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The design of reward functions in reinforcement learning is a human skill that comes with experience. Unfortunately, there is not any methodology in the literature that could guide a human to design the reward function or to allow a human to transfer the skills developed in designing reward functions to another human and in a systematic manner. In this paper, we use Systematic Instructional Design, an approach in human education, to engineer a machine education methodology to design reward functions for reinforcement learning. We demonstrate the methodology in designing a hierarchical genetic reinforcement learner that adopts a neural network representation to evolve a swarm controller for an agent shepherding a boids-based swarm. The results reveal that the methodology is able to guide the design of hierarchical reinforcement learners, with each model in the hierarchy learning incrementally through a multi-part reward function. The hierarchy acts as a decision fusion function that combines the individual behaviours and skills learnt by each instruction to create a smart shepherd to control the swarm.

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Machine Education: Designing semantically ordered and ontologically guided modular neural networks

Abbass

Elsawah

Petraki

et al. 2019

2019 IEEE Symposium Series on Computational Intelligence (SSCI)

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The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper, we first discuss selected attempts to date on machine teaching and education. We then bring theories and methodologies together from human education to structure and mathematically define the core problems in lesson design for machine education and the modelling approaches required to support the steps for machine education. Last, but not least, we offer an ontologybased methodology to guide the development of lesson plans to produce transparent and explainable modular learning machines, including neural networks.

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Instructional Design: International Perspectives

Cited by 4 publications

References 0 publications

Instructional Design Oriented Towards the Development of Competences

Instructional Design Oriented Towards the Development of Competences

Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding

Machine Education: Designing semantically ordered and ontologically guided modular neural networks

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