scholarly journals Simulating Digital Classics in Classical Teaching

2021 ◽  
pp. 117-128
Author(s):  
Corinna Reinhardt ◽  
Torsten Bendschus
Keyword(s):  
Process Model ◽  
Simulation Game ◽  
Academic Expectations ◽  
Assessment And Evaluation ◽  
Classical Archaeology ◽  
Teaching Concept ◽  
Interdisciplinary Research Project ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Digital Methods

In the 21st century, Classical Archaeology is making more and more use of digital tools and methods. This tendency towards a future field of “Digital Classics” requires participation not only as users, but also as developers. For this reason, the required qualification profile for a student of Classical Archaeology is changing and academic teaching at universities is confronted with new challenges. Our presentation tackles this issue by suggesting a new teaching concept that focuses especially on the pivotal skills that are needed to use and develop digital methods within an interdisciplinary team. It is based on the didactic model of a simulation game. This simulation is attached to a (real) interdisciplinary research project. In this way it offers the possibility of a structured process model and challenges the participants’ skills of interaction and complex decision-making. The result is a realistic environment whose demands, means and conditions of action support the assessment and evaluation of academic expectations in multidisciplinary professional situations

scholarly journals A Delphi Study Investigating Clinicians’ Views on Access to, Delivery of, and Adaptations of MBCT in the UK Clinical Settings

Mindfulness ◽  
2021 ◽  
Author(s):  
Kate Williams ◽  
Samantha Hartley ◽  
Peter Taylor
Keyword(s):  
Delphi Study ◽  
Good Practice ◽  
Evidence Base ◽  
Clinical Settings ◽  
Training Support ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Uk ◽  
Clinical Populations

Abstract Objectives Mindfulness-based cognitive therapy (MBCT) is a well-evidenced relapse-prevention intervention for depression with a growing evidence-base for use in other clinical populations. The UK initiatives have outlined plans for increasing access to MBCT in clinical settings, although evidence suggests that access remains limited. Given the increased popularity and access to MBCT, there may be deviations from the evidence-base and potential risks of harm. We aimed to understand what clinicians believe should be best clinical practice regarding access to, delivery of, and adaptations to MBCT. Methods We employed a two-stage Delphi methodology. First, to develop statements around best practices, we consulted five mindfulness-based experts and reviewed the literature. Second, a total of 59 statements were taken forward into three survey rating rounds. Results Twenty-nine clinicians completed round one, with 25 subsequently completing both rounds two and three. Forty-four statements reached consensus; 15 statements did not. Clinicians agreed with statements regarding sufficient preparation for accessing MBCT, adherence to the evidence-base and good practice guidelines, consideration of risks, sufficient access to training, support, and resources within services, and carefully considered adaptations. The consensus was not reached on statements which reflected a lack of evidence-base for specific clinical populations or the complex decision-making processes involved in delivering and making adaptations to MBCT. Conclusions Our findings highlight the delicate balance of maintaining a client-centred and transparent approach whilst adhering to the evidence-base in clinical decisions around access to, delivery of, and adaptations in MBCT and have important wide-reaching implications.

scholarly journals Goal-driven active learning

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Nicolas Bougie ◽  
Ryutaro Ichise
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Process ◽  
Real World ◽  
Imitation Learning ◽  
Learning Approaches ◽  
Wide Range ◽  
Fixed Set ◽  
Complex Decision Making ◽  
Complex Decision

AbstractDeep reinforcement learning methods have achieved significant successes in complex decision-making problems. In fact, they traditionally rely on well-designed extrinsic rewards, which limits their applicability to many real-world tasks where rewards are naturally sparse. While cloning behaviors provided by an expert is a promising approach to the exploration problem, learning from a fixed set of demonstrations may be impracticable due to lack of state coverage or distribution mismatch—when the learner’s goal deviates from the demonstrated behaviors. Besides, we are interested in learning how to reach a wide range of goals from the same set of demonstrations. In this work we propose a novel goal-conditioned method that leverages very small sets of goal-driven demonstrations to massively accelerate the learning process. Crucially, we introduce the concept of active goal-driven demonstrations to query the demonstrator only in hard-to-learn and uncertain regions of the state space. We further present a strategy for prioritizing sampling of goals where the disagreement between the expert and the policy is maximized. We evaluate our method on a variety of benchmark environments from the Mujoco domain. Experimental results show that our method outperforms prior imitation learning approaches in most of the tasks in terms of exploration efficiency and average scores.

Site controlling in infrastructure projects by digital methods

2021 ◽  
Author(s):  
Tino Walther ◽  
Marianne Pieper ◽  
Hans-Joachim Bargstädt
Keyword(s):  
Performance Measurement ◽  
Construction Industry ◽  
Process Model ◽  
Current Practice ◽  
Early Stage ◽  
Recommendations For Action ◽  
Digital Planning ◽  
The Status ◽  
Project Controlling ◽  
Digital Methods

<p>The construction industry is essentially determined by digital transformation and an increasingly complex market environment. Project controlling and monitoring is of high importance for construction site activities to achieve the project goals. Digital planning and recording methods make it possible to identify deviations at an early stage and to ensure the profitability of the project. To discuss the current practice of construction performance measurement as well as digital approaches in this domain, a qualitative study was carried out. The results of this empirical analysis examine the status quo of the construction performance measurement in civil engineering companies to illustrate the currently used methods and trends. Findings for the future use of digital planning and recording methods were obtained from the investigation. Based on empirical hypotheses, recommendations for action as well as for an improved process model are given.</p>

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