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A Systematic Approach for Designing Learning Environments for Energy Efficiency in Industrial Production
Available online at www.sciencedirect.com
ScienceDirect Procedia Manufacturing 9 (2017) 9 – 16
7th Conference on Learning Factories, CLF 2017
A systematic approach for designing learning environments for energy efficiency in industrial production Eberhard Abele, Dominik Flum*, Nina Strobel Institute of Production Management, Technology and Machine Tools (PTW), Otto -Berndt-Str. 2, 64287 Darmstadt
Abstract
Energy efficiency has been recognized in many manufacturing companies as an area of activity for cost savings and for environmental protection. Barriers, however, exist among others in the training of the employees. While at least larger companies have specialists and specialized departments, a holistic implementation is only possible with the involvement of all employees. The non-visibility and complexity of energy flows are challenging to impart knowledge illustratively. Furthermore, energy efficiency does not only require disciplinary but also interdisciplinary knowledge to exploit the energy efficiency potentials beyond the sy stem boundaries of a factory. By these challenges, the design of learning environments has special significance. This paper presents a systematic approach for the development of learning environments for energy efficiency in the industrial production. Depe nding on the addressed target group, the competences to be imparted are methodically transferred to design features of a learning environment. The result is an effective and target group-oriented development process. ©©2017 by Elsevier B.V. This is an open access article under the CC BY-NC-ND license 2016Published The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). of scientific the scientific committee 7th Conference on Learning Peer-review under responsibility Peer review under responsibility of the committee of the of 7ththe Conference on Learning FactoriesFactories. Keywords: Energy efficiency; Learning Factory; Action-oriented learning
1. Introduction As a result of the inception of the Paris Agreement on 4 November 2016, the decisions of the Paris Convention on Climate Change are now reality. States are henceforth required to develop action plans, how the binding international objectives can be achieved [1]. Germany has adopted the Climate Protection Plan 2050 in this context. Among other things, this includes the optimization of the continuous transfer of knowledge between universities and industry, so
* Corresponding author. Tel.: +49-6151-16-20110; fax: +49-6151-16-20087. E-mail address: [email protected]
2351-9789 © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer review under responsibility of the scientific committee of the 7th Conference on Learning Factories doi:10.1016/j.promfg.2017.04.001
10
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
that highly energy-efficient technologies are increasingly used in practice [2]. Action-oriented learning environments like Learning Factories are a key aspect to make the transfer of knowledge efficient [3]. Since energy efficiency is applied at all levels of the factory system, the learning environment must also reflect the corresponding hierarchical level. Not always, however, it is necessary to build a complete factory or a complete production system in order to offer the participants of a training course a appropriate learning environment. If sub-aspects like possibilities for increasing the energy efficiency of cross-sectional technologies (e.g. compressed air systems, electric drives, …) are considered, it will often be sufficient to use more compact learning stations . Developers of trainings and workshops in the area of energy efficiency have to decide how exactly they should design the physical learning environment. The approach presented in this paper supports developers in the progress of designing new learning environments. On the other hand, the approach can also be used for the assessment of already existing learning environments with regard to their suitability for training the desired target groups and contents. 2. Theoretical Background 2.1. Competence oriented learning and experiential education In the area of energy efficiency, it is particularly important not only to have theoretical knowledge, but to know methods how to apply it to the real application. Furthermore, it is crucial that people who are implementing energy efficiency measures in companies have the necessary motivation. Thus in trainings which are conducted in the learning environment or at a specific learning station, competences have to be generated instead of pure scientific knowledge. Competence models are today a key component of the personnel strategies of most companies and state of the art in the area of further education [4]. On the other hand, it is important in the field of energy efficiency to have at least a basic knowledge of the most important energy conversion technologies and to understand the physical principles of energy supply. Physical learning environments can make an important contribution to the visualization and linking of the theoretical content with practice, thus contributing to a higher effectiveness of learning [5]. Personal practical experiences ensure that learners can transfer acquired knowledge to their personal everyday life [6]. For this reason, it is important to make learning environments as practical as possible and at the same time to abstract them so that the learner can concentrate on the questions that are to be conveyed. In the approach presented in this paper, a guide is drawn up for the design of practice-oriented learning environments on the basis of the subject to be mediated and the external boundary conditions. 2.2 Learning environments Action-oriented learning environments facilitate the acquisition of competencies through a self-learning process. Especially in production technology, these practical learning environments are imple mented within the framework of Learning Factories. The difference to other teaching and learning formats is the realistic and changeable production process where not only lecturing, but learning methods like realistic simulations of production systems are utilized to enhance the trainees’s learning experience. This allows for a production -technological competency obtainment in a learning environment that is close to the realistic work process. However, in case of energy efficiency, the challenge is to create the balancing act between the illustration of energy and the prevention of realistic working conditions [7]. For example, energy flows like heat or electrical current are not visible and have to be perceptible, on the one hand, for a lasting knowledge transfer. On the other hand, the processes must not be too abstracted to achieve the transfer into practice. The development of learning environments for energy efficiency is therefore a particular challenge. The proposed approach is based on the findings of [8] and [9] but is focusing on physical learning environments particularly for the topic of energy efficiency. The user friendliness is increased since no didactic knowledge is required for using the guide. Instead the LE³ (Learning Environment for Energy Efficiency)-Guide is especially addressing technical experts and planners (e.g. developers of energy efficient technologies, production planners).
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Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
3. The LE³-Gui de The LE³-Guide (Fig. 1) offers a systematic approach for developing target-group oriented learning environments for energy efficiency. The basic idea of the LE³-Guide is to provide a learning environment design which suits the transfer of required knowledge for a certain target group of trainees. Starting point is the designer of the intended learning environment. In case of energy efficiency, learning environments have mainly the objective to impart optimization measures to a certain target group. The designer of the learning environment is therefore in many occasions not a didactics specialist but an engineer who is well-qualified in energy efficiency topics but not in disseminating knowledge. This is where the guide starts by giving the developer support in considering didactic principles. In the end, however, the developer has the choice whether and how he would implement the suggestions of the guide.
Learning Environment Designer 1 Questionnaire I: General Conditions
Purpose
Target Group
Resources
6
2 Basic Type of LE
Learning Objectives 3 & Design Features
Check List 5 Requirements Catalogue
Questionnaire II: Learning 4 Objectives & Design Features
Prioritized Learning Objectives
Features & Specifications
Fig. 1: LE³-Guide
To ensure a high level of user friendliness all the required information are gathered through questionnaires. There are two crucial inputs from the user side. The first questionnaire focuses on the general conditions whereas the second questionnaire is specifying the details. According to the answers given by the user, the intended learning environment is classified into a category that is associated with learning objectives and design features. The individual steps of the LE³-Guide are presented below. 3.1. Questionnaire I – General Conditions In many occasions, not all of the general conditions are obvious to t he learning environment designer. Especially the general objectives and the target group are oftentimes vague in the beginning of the design process. Therefore, a questionnaire is part of the guideline helping to clarify these aspects. It is the first step of the LE³-Guide that supports the designer in defining the fundamentals of the learning environment. These are composed by the following aspects: purpose, target group, budget, time frame and spatial resources . Additionally, the questionnaire draws attention to
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Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
aspects that should be taken into consideration for the design. Depending on the results of the questionnaire, the intended learning environment is assigned to one of pre-defined, basic types of learning environments. 3.2. Categories of learning environments The basic types of learning environment describe categorical classifications of potential learning environments. Each type of a learning environment is related, on the one hand, to certain learning objectives that should be covered for the identified target group. On the other hand, possible (design) features of the learning environmen t are proposed to the designer. For that, four general purposes for learning environments were determined: Fascination, Sensitization, Analyzation and Transformation. A fascinating learning environment has the main objective to attract attention. The focus is mainly on a single aspect. The content is easy to understand and triggers a wo w effect. In contrast, a sensitizing learning environment strives to point out the importance of an issue. A wow effect is to be generated too, but is more influenced by the content. With a learning environment for analyzations, a deeper understanding of the content should be established. For that, the trainees try out theoretical parts of a trainings course directly in the learning environment. The direct application of the training content in the industrial practice is the main goal of a learning environment for transformation. To increase energy efficiency many interactions in a system must be considered. Therefore, not only a deep understanding of the content is necessary, but also a linking of the aspects. It is equally important that the training participants are empowered to pass on the findings to colleagues. A further dimension for classifying a learning environment is the target group that is trained. It is mainly dete rmined by the prior knowledge. Alien to subject
Beginner
Advanced
Expert
Fascination
A1
A1
B2
B3
Sensitization
B1
B1
B2
B3
C1
C2
C2
D1
D2
Analyzation Transformation Fig. 2: Learning environment type determination matrix
According to the two dimensions, eight general types of learning environments were defined (Fig. 2). In case of contrary objectives (e.g. inhomogeneous target groups), several categories can be considered according to the first questionnaire. In this case, it must be decided whether it might be useful to integrate several different learning stations with different degrees of detail into the learning environment. Another possibility is to design individual learning stations in such a way that they can be converted from one category to the o ther and thus adapted to the respective target group. T able 1. Basic types of learning environment and relation to results of questionnaire Basic T ype
Description
Achieved points / answered questions
A1
Basically draw attention to the topic for people who have little to no prior knowledge
< 1,3
B1
Affect day-to-day behavior of people who have little or no prior knowledge
< 1,7
B2
Draw attention & affect day-to-day behavior of people who already have prior knowledge
<2
B3
Draw attention & affect day-to-day behavior of people who already have a lot of prior knowledge
< 2,3
C1
Develop a deep understanding of the content, if there is little prior knowledge
< 2,7
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Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
C2
Develop a deep understanding of the content, if there is already prior knowledge
<3
D1
General topics: Transfer functional relationships to industrial practice or to comparable issues & impart knowledge to colleagues
< 3,3
D2
Specific topics: Transfer functional relationships to industrial practice or to comparable issues & impart knowledge to colleagues
>3,3
Aliens to the energy efficiency topic are unlikely trained for an analyzation or transformation purpose. The same applies for beginners and transformation. A fascinating learning environment for aliens to subject and beginners does not differ significantly. In order to keep the complexity low, these and other groups were combined. Depending on how the questions are ans wered in the questionnaire, the type of learning environment is defined (Table 1). Each type that is linked with a number of learning objectives that can be understood as suggestions. 3.3. Learning objectives and Design Features The training curriculum of the ETA Learning Factory is based on a list of learning objectives for an energy efficient production [10]. These learning objectives are obtained from different training modules that can be basically clustered in Motivation, Fundamentals and Tools & Techniques. The clusters comprise both technical and organizational energy efficiency measures and act on all levels, from the component up to the whole factory system. Learning objectives from the cluster Motivation strive to engage people for the topic of energy efficiency and include economic, ecologic and regulatory fields of action. In Fundamentals the physical and technical basics are listed. The learning objectives are, on the one hand, generally held, but also specific to the technology. In order to identify an d raise energy efficiency potentials, methods were developed and complemented with existing tools in the cluster Tools & Techniques. A learning environment has to be associated with clear learning objectives. Therefore, the basic types of learning environments are linked with appropriate learning objectives of the ETA Learning Factory curriculum (Fig. 3). Learning objectives for energy efficiency
Fascination A1
Sensitization B1
B2
Analyzation B3
C1
C2
Transformation D1
Motivation Typical energy costs related to the technology known Energy efficiency potentials in the subject known
X X
X
X
etc.
Fundamentals Important physical factors and units known
X
Types of energy waste
X
etc.
Tools & Techniques Sankey Theoretical Limit etc.
Fig. 3: Learning objectives (extract)
X X
D2
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Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
Besides the learning objectives the LE³-Guide provides basic information on the (design) features of the learning environment. Nine features for describing the design were identified (Fig. 4). Important for a learning environment for energy efficiency is the tangibility of energy. Seeing, hearing and feeling energy and energy flows are fundamen tal aspects to make the learning environment perceptible. For each feature, four specifications were derived that principally come into question.
Feature
Specification Schematic without reference to a product
Functional with a fantasy product
Realistic with real product category
One-to-one mapping with real product
Without interaction
moderated
Individual informing
Autonomous problemsolving
Complexity
Directly apparent
Easy to understand
Comprehensible
Complex
Modularity
Inflexible
Exchangeable
Expandable
Reconfigurable
Not mobile
Movable
Transportable
Mobile and Compact
Static
Dynamic
Augmented reality
Completely virtual
Abstraction level Extent of participation
Transportability Visualization (energy) Fig. 4: Morphological box (extract)
The selection of a specification depends on the results of the questionnaire. In many cases not a definite specification can be indicated but a range or tendency. 3.4. Questionnaire II: Tailoring to the use case Since it is not possible to entirely define the learning objectives as an external consultant, the list of learning objectives is a suggestion of possible topics in the first place. The designer has to prioritize at last which learning objective and how many are sensible for his learning environment. In addition, the physical design of the learning environment depends on boundary conditions like financial, spatial and material resources as well as the required time effort. The tailoring step of the LE³-Guide consists of a second (smaller) questionnaire that helps to prioritize the design features of the learning environment. The result is a prioritization of the learning objectives decided by the user and a prioritization of the physical design features as a result of the questionnaire in the categories A, B, and C. 3.5. Requirements catalogue The results of the LE3-Gu ide are summarized in a requirements catalog (Fig. 5) that consists of the prioritized learning objectives and the design features of the intended learning environment. This listing represents a proposal that should be covered by an ideal learning environment. This ideal conception serves on the one hand as an aid to new developments by identifying aspects to be taken into consideration from a didactic point of view (greenfield application). On the other hand, the ideal image can be used as a blueprint for the evaluation of existing learning environments (brownfield application). For that, the requirements catalogue has two columns where the degree of fulfillment of the corresponding learning objective or design feature can be entered. In the case of a greenfield application, these columns remains free. 3.6. Check list The check list consists of matters that are oftentimes forgotten at the beginning of a realization process of learning environments. Therefore, it represents a reminder for the developer which contains inter alia the following aspects:
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
required connections (electricity, water, pressurized air, internet, etc.), staff required for operating the learning environment during the trainings cours e, maintenance effort. 4. Brownfield Application of the LE³-guide: Learning station for a hydraulic system of machine tools There are two application scenarios conceivable of the LE³-Guide. The first scenario is the most obvious and addresses the design process of a completely new learning environment. But there is also an application for the evaluation and improvement of existing learning environments which is to be explained in the following use case. The ETA Learning Factory is not exclusively for trainings but is primarily a large-scale research demonstrator. Therefore, the training curriculum is highly influenced by new research results. One example is a technology demonstrator depicting a hydraulic system of a machine tool. Due to the high complexity, the focus was initially on
Fig. 5: Requirements catalogue as a reference for improvements with evaluation of an existing learning station for hydraulic systems
the technical operability of the system. Didactic subjects were secondary in the design process. The main objective of the demonstrator was the application as a learning environment to illustrate energy efficiency potentials of a hydraulic system. For that, different design options can be set and compared in terms of the energy consumption. Since didactic subjects were neglected, it was not possible to use the demonstrator in the training curriculum at first. With the LE³-
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Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
Guide, however, it was possible to systematically identify improvement potentials of the learning environment. The guide was used in a reverse engineering style in which the existing version was ignored at first. The result is the requirements catalogue of the ideal learning environment for the hydraulic system. By comparing this ideal reference with the actual design, it can be assessed whether the learning environment is in principle suited to convey the learning objectives (DoF_1). After that, each required design feature can be checked for the degree of fulfillment (DoF_2). According to the prioritization of the criterion, the evaluation is multiplied by a factor of 1 (prio. C), 2 (prio. B) or 3 (prio. A). Based on the total number of points achieved, the need for action is derived. The assessment of the individual criteria in turn reveals where concrete potential for improvement exists. For the hydraulic system, major need for action has been identified in the field of design features. In order to be able to use the demonstrator within the framework of training courses, it is necessary to imp rove the intelligibility. For the sake of improvement, a visualization of the entire measurement data is implemented on a dashboard. In addition, a visualization of the functional principle is introduced in the form of schematic sketches. This is the basis for the fact that the trainee's involvement can also be increased. For that, the control of the demonstrator will be transferred to a SCADA (Supervisory Control and Data Acquisition) platform so that it can be controlled via mobile devices. 5. Conclusion and Outlook The introduced LE³-Guide offers a new and systematic approach for developing target -group oriented learning environments for energy efficiency. It supports the designer of a learning environment that is in many occasions not familiar with didactic but with energy efficiency principles. Therefore, it addresses the problems of lacking target group orientation and intelligibility. Its use is not limited to greenfield developments, but is also possible with existing installations. The results of the use case show the potential for an application for evaluating and improving learning environments. While the procedure of the guide is currently working manually and not without guidance, an implementation as a software tool is aspired. This would greatly improve the user friendliness and the results analysis which would contribute to a further spread of the LE³-Guide. References [1] United Nations, „Paris Agreement - Status of Ratification,“ 13 December 2016. [Online]. Available: http://unfccc.int/paris_agreement/items/9444.php. [2] BMUB, Klimaschutzplan 2050 - Klimapolitische Grundsätze und Ziele der Bundesregierung, Berlin, 2016. [3] W. Sinh, D. Gerhard und F. Bleicher, „Vision and implementation of the Learning and Innovation Factory of the Vienna University of Technology,“ 2nd Conference on Learning Factories, pp. 160-177, 2012. [4] J. Erpenbeck und L. Rosenstiel, Handbuch Kompetenzmessung, Stuttgart: Schäffer-Poeschel, 2007. [5] R. Lowe, „Interrogation of a dynamic visualization during learning,“ Learning and Instruction, pp. 257-74, 2004. [6] R. Carver, „Theory for practice: A framework for thinking about experiential education,“ Journal of Experiential Education 19 (I), pp. 8-13, 1996. [7] A. Kaluza, M. Juraschek, B. Neef, R. Pittschellis, G. Posselt und S. Thiede, „Designing Learning Environments for Energy Efficiency trough Model Scale Production Processes,“ Procedia CIRP, pp. 32:41-6, 2015. [8] M. Abel, S. Czajkowski, L. Faatz, J. Metternich und R. Tenberg, „Kompetenzorientiertes Curriculum für Lernfabriken: Ein diaktisch hinterlegtes Konzept für Lernfabriken,“ Werkstatttechnik online, pp. 240-5, 2013. [9] M. Tisch, C. Hertle, J. Cachay, E. Abele, J. Metternich und R. Tenberg, „A systematic Approach on Developing Action-oriented, Competenca-based Learning Factories,“ Procedia CIRP, pp. 7:580-5, 2013. [10] E. Abele, C. Bauerdick, N. Strobel und N. Panten, „ETA Learning Factory: A holistic Con cept for teaching Energy Efficiency in Production,“ Procedia CIRP - 6th Conference on Learning Factories, 2016.
ScienceDirect Procedia Manufacturing 9 (2017) 9 – 16
7th Conference on Learning Factories, CLF 2017
A systematic approach for designing learning environments for energy efficiency in industrial production Eberhard Abele, Dominik Flum*, Nina Strobel Institute of Production Management, Technology and Machine Tools (PTW), Otto -Berndt-Str. 2, 64287 Darmstadt
Abstract
Energy efficiency has been recognized in many manufacturing companies as an area of activity for cost savings and for environmental protection. Barriers, however, exist among others in the training of the employees. While at least larger companies have specialists and specialized departments, a holistic implementation is only possible with the involvement of all employees. The non-visibility and complexity of energy flows are challenging to impart knowledge illustratively. Furthermore, energy efficiency does not only require disciplinary but also interdisciplinary knowledge to exploit the energy efficiency potentials beyond the sy stem boundaries of a factory. By these challenges, the design of learning environments has special significance. This paper presents a systematic approach for the development of learning environments for energy efficiency in the industrial production. Depe nding on the addressed target group, the competences to be imparted are methodically transferred to design features of a learning environment. The result is an effective and target group-oriented development process. ©©2017 by Elsevier B.V. This is an open access article under the CC BY-NC-ND license 2016Published The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). of scientific the scientific committee 7th Conference on Learning Peer-review under responsibility Peer review under responsibility of the committee of the of 7ththe Conference on Learning FactoriesFactories. Keywords: Energy efficiency; Learning Factory; Action-oriented learning
1. Introduction As a result of the inception of the Paris Agreement on 4 November 2016, the decisions of the Paris Convention on Climate Change are now reality. States are henceforth required to develop action plans, how the binding international objectives can be achieved [1]. Germany has adopted the Climate Protection Plan 2050 in this context. Among other things, this includes the optimization of the continuous transfer of knowledge between universities and industry, so
* Corresponding author. Tel.: +49-6151-16-20110; fax: +49-6151-16-20087. E-mail address: [email protected]
2351-9789 © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer review under responsibility of the scientific committee of the 7th Conference on Learning Factories doi:10.1016/j.promfg.2017.04.001
10
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
that highly energy-efficient technologies are increasingly used in practice [2]. Action-oriented learning environments like Learning Factories are a key aspect to make the transfer of knowledge efficient [3]. Since energy efficiency is applied at all levels of the factory system, the learning environment must also reflect the corresponding hierarchical level. Not always, however, it is necessary to build a complete factory or a complete production system in order to offer the participants of a training course a appropriate learning environment. If sub-aspects like possibilities for increasing the energy efficiency of cross-sectional technologies (e.g. compressed air systems, electric drives, …) are considered, it will often be sufficient to use more compact learning stations . Developers of trainings and workshops in the area of energy efficiency have to decide how exactly they should design the physical learning environment. The approach presented in this paper supports developers in the progress of designing new learning environments. On the other hand, the approach can also be used for the assessment of already existing learning environments with regard to their suitability for training the desired target groups and contents. 2. Theoretical Background 2.1. Competence oriented learning and experiential education In the area of energy efficiency, it is particularly important not only to have theoretical knowledge, but to know methods how to apply it to the real application. Furthermore, it is crucial that people who are implementing energy efficiency measures in companies have the necessary motivation. Thus in trainings which are conducted in the learning environment or at a specific learning station, competences have to be generated instead of pure scientific knowledge. Competence models are today a key component of the personnel strategies of most companies and state of the art in the area of further education [4]. On the other hand, it is important in the field of energy efficiency to have at least a basic knowledge of the most important energy conversion technologies and to understand the physical principles of energy supply. Physical learning environments can make an important contribution to the visualization and linking of the theoretical content with practice, thus contributing to a higher effectiveness of learning [5]. Personal practical experiences ensure that learners can transfer acquired knowledge to their personal everyday life [6]. For this reason, it is important to make learning environments as practical as possible and at the same time to abstract them so that the learner can concentrate on the questions that are to be conveyed. In the approach presented in this paper, a guide is drawn up for the design of practice-oriented learning environments on the basis of the subject to be mediated and the external boundary conditions. 2.2 Learning environments Action-oriented learning environments facilitate the acquisition of competencies through a self-learning process. Especially in production technology, these practical learning environments are imple mented within the framework of Learning Factories. The difference to other teaching and learning formats is the realistic and changeable production process where not only lecturing, but learning methods like realistic simulations of production systems are utilized to enhance the trainees’s learning experience. This allows for a production -technological competency obtainment in a learning environment that is close to the realistic work process. However, in case of energy efficiency, the challenge is to create the balancing act between the illustration of energy and the prevention of realistic working conditions [7]. For example, energy flows like heat or electrical current are not visible and have to be perceptible, on the one hand, for a lasting knowledge transfer. On the other hand, the processes must not be too abstracted to achieve the transfer into practice. The development of learning environments for energy efficiency is therefore a particular challenge. The proposed approach is based on the findings of [8] and [9] but is focusing on physical learning environments particularly for the topic of energy efficiency. The user friendliness is increased since no didactic knowledge is required for using the guide. Instead the LE³ (Learning Environment for Energy Efficiency)-Guide is especially addressing technical experts and planners (e.g. developers of energy efficient technologies, production planners).
11
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
3. The LE³-Gui de The LE³-Guide (Fig. 1) offers a systematic approach for developing target-group oriented learning environments for energy efficiency. The basic idea of the LE³-Guide is to provide a learning environment design which suits the transfer of required knowledge for a certain target group of trainees. Starting point is the designer of the intended learning environment. In case of energy efficiency, learning environments have mainly the objective to impart optimization measures to a certain target group. The designer of the learning environment is therefore in many occasions not a didactics specialist but an engineer who is well-qualified in energy efficiency topics but not in disseminating knowledge. This is where the guide starts by giving the developer support in considering didactic principles. In the end, however, the developer has the choice whether and how he would implement the suggestions of the guide.
Learning Environment Designer 1 Questionnaire I: General Conditions
Purpose
Target Group
Resources
6
2 Basic Type of LE
Learning Objectives 3 & Design Features
Check List 5 Requirements Catalogue
Questionnaire II: Learning 4 Objectives & Design Features
Prioritized Learning Objectives
Features & Specifications
Fig. 1: LE³-Guide
To ensure a high level of user friendliness all the required information are gathered through questionnaires. There are two crucial inputs from the user side. The first questionnaire focuses on the general conditions whereas the second questionnaire is specifying the details. According to the answers given by the user, the intended learning environment is classified into a category that is associated with learning objectives and design features. The individual steps of the LE³-Guide are presented below. 3.1. Questionnaire I – General Conditions In many occasions, not all of the general conditions are obvious to t he learning environment designer. Especially the general objectives and the target group are oftentimes vague in the beginning of the design process. Therefore, a questionnaire is part of the guideline helping to clarify these aspects. It is the first step of the LE³-Guide that supports the designer in defining the fundamentals of the learning environment. These are composed by the following aspects: purpose, target group, budget, time frame and spatial resources . Additionally, the questionnaire draws attention to
12
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
aspects that should be taken into consideration for the design. Depending on the results of the questionnaire, the intended learning environment is assigned to one of pre-defined, basic types of learning environments. 3.2. Categories of learning environments The basic types of learning environment describe categorical classifications of potential learning environments. Each type of a learning environment is related, on the one hand, to certain learning objectives that should be covered for the identified target group. On the other hand, possible (design) features of the learning environmen t are proposed to the designer. For that, four general purposes for learning environments were determined: Fascination, Sensitization, Analyzation and Transformation. A fascinating learning environment has the main objective to attract attention. The focus is mainly on a single aspect. The content is easy to understand and triggers a wo w effect. In contrast, a sensitizing learning environment strives to point out the importance of an issue. A wow effect is to be generated too, but is more influenced by the content. With a learning environment for analyzations, a deeper understanding of the content should be established. For that, the trainees try out theoretical parts of a trainings course directly in the learning environment. The direct application of the training content in the industrial practice is the main goal of a learning environment for transformation. To increase energy efficiency many interactions in a system must be considered. Therefore, not only a deep understanding of the content is necessary, but also a linking of the aspects. It is equally important that the training participants are empowered to pass on the findings to colleagues. A further dimension for classifying a learning environment is the target group that is trained. It is mainly dete rmined by the prior knowledge. Alien to subject
Beginner
Advanced
Expert
Fascination
A1
A1
B2
B3
Sensitization
B1
B1
B2
B3
C1
C2
C2
D1
D2
Analyzation Transformation Fig. 2: Learning environment type determination matrix
According to the two dimensions, eight general types of learning environments were defined (Fig. 2). In case of contrary objectives (e.g. inhomogeneous target groups), several categories can be considered according to the first questionnaire. In this case, it must be decided whether it might be useful to integrate several different learning stations with different degrees of detail into the learning environment. Another possibility is to design individual learning stations in such a way that they can be converted from one category to the o ther and thus adapted to the respective target group. T able 1. Basic types of learning environment and relation to results of questionnaire Basic T ype
Description
Achieved points / answered questions
A1
Basically draw attention to the topic for people who have little to no prior knowledge
< 1,3
B1
Affect day-to-day behavior of people who have little or no prior knowledge
< 1,7
B2
Draw attention & affect day-to-day behavior of people who already have prior knowledge
<2
B3
Draw attention & affect day-to-day behavior of people who already have a lot of prior knowledge
< 2,3
C1
Develop a deep understanding of the content, if there is little prior knowledge
< 2,7
13
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
C2
Develop a deep understanding of the content, if there is already prior knowledge
<3
D1
General topics: Transfer functional relationships to industrial practice or to comparable issues & impart knowledge to colleagues
< 3,3
D2
Specific topics: Transfer functional relationships to industrial practice or to comparable issues & impart knowledge to colleagues
>3,3
Aliens to the energy efficiency topic are unlikely trained for an analyzation or transformation purpose. The same applies for beginners and transformation. A fascinating learning environment for aliens to subject and beginners does not differ significantly. In order to keep the complexity low, these and other groups were combined. Depending on how the questions are ans wered in the questionnaire, the type of learning environment is defined (Table 1). Each type that is linked with a number of learning objectives that can be understood as suggestions. 3.3. Learning objectives and Design Features The training curriculum of the ETA Learning Factory is based on a list of learning objectives for an energy efficient production [10]. These learning objectives are obtained from different training modules that can be basically clustered in Motivation, Fundamentals and Tools & Techniques. The clusters comprise both technical and organizational energy efficiency measures and act on all levels, from the component up to the whole factory system. Learning objectives from the cluster Motivation strive to engage people for the topic of energy efficiency and include economic, ecologic and regulatory fields of action. In Fundamentals the physical and technical basics are listed. The learning objectives are, on the one hand, generally held, but also specific to the technology. In order to identify an d raise energy efficiency potentials, methods were developed and complemented with existing tools in the cluster Tools & Techniques. A learning environment has to be associated with clear learning objectives. Therefore, the basic types of learning environments are linked with appropriate learning objectives of the ETA Learning Factory curriculum (Fig. 3). Learning objectives for energy efficiency
Fascination A1
Sensitization B1
B2
Analyzation B3
C1
C2
Transformation D1
Motivation Typical energy costs related to the technology known Energy efficiency potentials in the subject known
X X
X
X
etc.
Fundamentals Important physical factors and units known
X
Types of energy waste
X
etc.
Tools & Techniques Sankey Theoretical Limit etc.
Fig. 3: Learning objectives (extract)
X X
D2
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Besides the learning objectives the LE³-Guide provides basic information on the (design) features of the learning environment. Nine features for describing the design were identified (Fig. 4). Important for a learning environment for energy efficiency is the tangibility of energy. Seeing, hearing and feeling energy and energy flows are fundamen tal aspects to make the learning environment perceptible. For each feature, four specifications were derived that principally come into question.
Feature
Specification Schematic without reference to a product
Functional with a fantasy product
Realistic with real product category
One-to-one mapping with real product
Without interaction
moderated
Individual informing
Autonomous problemsolving
Complexity
Directly apparent
Easy to understand
Comprehensible
Complex
Modularity
Inflexible
Exchangeable
Expandable
Reconfigurable
Not mobile
Movable
Transportable
Mobile and Compact
Static
Dynamic
Augmented reality
Completely virtual
Abstraction level Extent of participation
Transportability Visualization (energy) Fig. 4: Morphological box (extract)
The selection of a specification depends on the results of the questionnaire. In many cases not a definite specification can be indicated but a range or tendency. 3.4. Questionnaire II: Tailoring to the use case Since it is not possible to entirely define the learning objectives as an external consultant, the list of learning objectives is a suggestion of possible topics in the first place. The designer has to prioritize at last which learning objective and how many are sensible for his learning environment. In addition, the physical design of the learning environment depends on boundary conditions like financial, spatial and material resources as well as the required time effort. The tailoring step of the LE³-Guide consists of a second (smaller) questionnaire that helps to prioritize the design features of the learning environment. The result is a prioritization of the learning objectives decided by the user and a prioritization of the physical design features as a result of the questionnaire in the categories A, B, and C. 3.5. Requirements catalogue The results of the LE3-Gu ide are summarized in a requirements catalog (Fig. 5) that consists of the prioritized learning objectives and the design features of the intended learning environment. This listing represents a proposal that should be covered by an ideal learning environment. This ideal conception serves on the one hand as an aid to new developments by identifying aspects to be taken into consideration from a didactic point of view (greenfield application). On the other hand, the ideal image can be used as a blueprint for the evaluation of existing learning environments (brownfield application). For that, the requirements catalogue has two columns where the degree of fulfillment of the corresponding learning objective or design feature can be entered. In the case of a greenfield application, these columns remains free. 3.6. Check list The check list consists of matters that are oftentimes forgotten at the beginning of a realization process of learning environments. Therefore, it represents a reminder for the developer which contains inter alia the following aspects:
Eberhard Abele et al. / Procedia Manufacturing 9 (2017) 9 – 16
required connections (electricity, water, pressurized air, internet, etc.), staff required for operating the learning environment during the trainings cours e, maintenance effort. 4. Brownfield Application of the LE³-guide: Learning station for a hydraulic system of machine tools There are two application scenarios conceivable of the LE³-Guide. The first scenario is the most obvious and addresses the design process of a completely new learning environment. But there is also an application for the evaluation and improvement of existing learning environments which is to be explained in the following use case. The ETA Learning Factory is not exclusively for trainings but is primarily a large-scale research demonstrator. Therefore, the training curriculum is highly influenced by new research results. One example is a technology demonstrator depicting a hydraulic system of a machine tool. Due to the high complexity, the focus was initially on
Fig. 5: Requirements catalogue as a reference for improvements with evaluation of an existing learning station for hydraulic systems
the technical operability of the system. Didactic subjects were secondary in the design process. The main objective of the demonstrator was the application as a learning environment to illustrate energy efficiency potentials of a hydraulic system. For that, different design options can be set and compared in terms of the energy consumption. Since didactic subjects were neglected, it was not possible to use the demonstrator in the training curriculum at first. With the LE³-
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Guide, however, it was possible to systematically identify improvement potentials of the learning environment. The guide was used in a reverse engineering style in which the existing version was ignored at first. The result is the requirements catalogue of the ideal learning environment for the hydraulic system. By comparing this ideal reference with the actual design, it can be assessed whether the learning environment is in principle suited to convey the learning objectives (DoF_1). After that, each required design feature can be checked for the degree of fulfillment (DoF_2). According to the prioritization of the criterion, the evaluation is multiplied by a factor of 1 (prio. C), 2 (prio. B) or 3 (prio. A). Based on the total number of points achieved, the need for action is derived. The assessment of the individual criteria in turn reveals where concrete potential for improvement exists. For the hydraulic system, major need for action has been identified in the field of design features. In order to be able to use the demonstrator within the framework of training courses, it is necessary to imp rove the intelligibility. For the sake of improvement, a visualization of the entire measurement data is implemented on a dashboard. In addition, a visualization of the functional principle is introduced in the form of schematic sketches. This is the basis for the fact that the trainee's involvement can also be increased. For that, the control of the demonstrator will be transferred to a SCADA (Supervisory Control and Data Acquisition) platform so that it can be controlled via mobile devices. 5. Conclusion and Outlook The introduced LE³-Guide offers a new and systematic approach for developing target -group oriented learning environments for energy efficiency. It supports the designer of a learning environment that is in many occasions not familiar with didactic but with energy efficiency principles. Therefore, it addresses the problems of lacking target group orientation and intelligibility. Its use is not limited to greenfield developments, but is also possible with existing installations. The results of the use case show the potential for an application for evaluating and improving learning environments. While the procedure of the guide is currently working manually and not without guidance, an implementation as a software tool is aspired. This would greatly improve the user friendliness and the results analysis which would contribute to a further spread of the LE³-Guide. References [1] United Nations, „Paris Agreement - Status of Ratification,“ 13 December 2016. [Online]. Available: http://unfccc.int/paris_agreement/items/9444.php. [2] BMUB, Klimaschutzplan 2050 - Klimapolitische Grundsätze und Ziele der Bundesregierung, Berlin, 2016. [3] W. Sinh, D. Gerhard und F. Bleicher, „Vision and implementation of the Learning and Innovation Factory of the Vienna University of Technology,“ 2nd Conference on Learning Factories, pp. 160-177, 2012. [4] J. Erpenbeck und L. Rosenstiel, Handbuch Kompetenzmessung, Stuttgart: Schäffer-Poeschel, 2007. [5] R. Lowe, „Interrogation of a dynamic visualization during learning,“ Learning and Instruction, pp. 257-74, 2004. [6] R. Carver, „Theory for practice: A framework for thinking about experiential education,“ Journal of Experiential Education 19 (I), pp. 8-13, 1996. [7] A. Kaluza, M. Juraschek, B. Neef, R. Pittschellis, G. Posselt und S. Thiede, „Designing Learning Environments for Energy Efficiency trough Model Scale Production Processes,“ Procedia CIRP, pp. 32:41-6, 2015. [8] M. Abel, S. Czajkowski, L. Faatz, J. Metternich und R. Tenberg, „Kompetenzorientiertes Curriculum für Lernfabriken: Ein diaktisch hinterlegtes Konzept für Lernfabriken,“ Werkstatttechnik online, pp. 240-5, 2013. [9] M. Tisch, C. Hertle, J. Cachay, E. Abele, J. Metternich und R. Tenberg, „A systematic Approach on Developing Action-oriented, Competenca-based Learning Factories,“ Procedia CIRP, pp. 7:580-5, 2013. [10] E. Abele, C. Bauerdick, N. Strobel und N. Panten, „ETA Learning Factory: A holistic Con cept for teaching Energy Efficiency in Production,“ Procedia CIRP - 6th Conference on Learning Factories, 2016.