In the previous section it has been described how SRL can be operationalised. In this section concrete approaches are reported how SRL is supported by using the models and framework described above. They establish the ground basis for the technology and concepts to support learners in a scientifically driven way and provide learners with according technology and material to guide them through the learning process.
Learners who are able to understand the SRL process and the related learning activities and who are able to perform them on their own can navigate freely through their learning processes. However, this requires the availability of a high degree of SRL capabilities (availability of the respective SRL competences). Since it cannot be assumed that all learners already have these abilities, guidance mechanisms are needed. Such guidance is often needed especially when learning with technology-enhanced environments (Bannert 2006).
According to the experiences made in the test beds and at several workshops (see section “Related Work and Technology”), a variety of guidance strategies is necessary. Both technical and human support is needed depending on the learner and the situation. Additionally training and introductory material turned out as useful to increase initial motivation for new ways of learning.
Motivational Video
This section explains an initiative to make learners acquainted with SRL. According to our experience (in test beds and SRL surveys), the concept of SRL is new to most lectures and learners. Lifelong learning, non-formal learning, etc. are buzz words society talks about, but SRL is apparently a term more common in science and pedagogical research. For this reason, SRL needs to be introduced and actually promoted to learners, teachers, and a broader community to point out benefits of such a learning approach. An introduction can be done in many different ways.
Teaser videos were used to explain the concept of SRL on a basic level for learners who are completely new to SRL. A videoFootnote 7 has been created that focuses on the explanation of SRL by comparing it to a city travel (see Fig. 6). Two people are examining a city and its sights. While the first one is attending a guided tour, the second one defines the goals and plans on his own and does a city walk without external support. This analogy is explaining both the concept of self-regulation and the concept of guidance. Further videos have been developed in the course of the ROLE project, in order to explain different aspects of PLEs and SRLFootnote 8. Especially, tutorial videos have been created that explain how to use ROLE technology.
Courses and Training Material
An SRL course is another method to reach learners and provide them with assistance and knowledge about SRL and SRL tools in a compact way. The goals of such a course are to introduce the idea of SRL and enable them to build their own learning environment. The content of such a course can be a brief SRL explanation, an explanation of different learning models or learning strategies, and how they can be used with ROLE technology.
At the Open University UK test bed such a course has been created as Online Course and as eBook. This course explains the basic concepts and also lets learners try out to create PLEs on their own. In this way learners can train SRL behaviour because they get step-by-step explanation and can try it out immediately.
Preconfigured PLEs
Predefined PLEs are already compiled bundles of widgets to fulfil a certain learning need. Therefore, they are usually assembled with widgets that cover a certain domain (e.g. history, chemistry, or language learning). Such bundles are typically created by teachers or peers. Teachers have the chance to prepare a bundle suitable for the learning topic. In this way, the guidance is based on the preparation of whole bundles that are suitable for individual learners. A special case is Layered PLEs that consists of a set of widget bundles. Each set may be dedicated to a certain learning strategy of an SRL process phase.
Widget Store
The ROLE Widget Store is a Web-based online catalogue that allows to manage and index widgets. It provides a user-friendly interface to a widget repository that simplifies the discovery of widgets. The functionality of the widget store includes listings of widgets, categorisations, searching by widgets or keywords, and compilation of widgets into bundles. Users can add widgets from the widget store to PLE systems. From a social media point of view, the store is also the place to collect and share user tags, comments, and ratings. A widget creator and developer can add a widget to the store by adding its reference (URL) and metadata.
In order to provide guidance for learners in searching and selecting widgets for their PLEs, widgets can be tagged with metadata describing the purpose of the widgets. The first type of tags is a widget categorisation consisting of seven categories. The categories were derived from the SRL learning process model and are assigned to its phases. As described above a PLE should consist of widgets not only for one learning strategy, but widgets for different strategies should be included. The categorisation system is a useful way to follow this guideline because users get quick access to widgets for the specific purposes. They can browse the store and add widgets just by navigating to different categories.
In addition to the widget categories, functionalities described in an ontology are used to represent features of widgets (e.g. text editing, video chat). These functionalities are derived from a survey of existing widgets and from an analysis of the ontology. The SRL techniques are related to functionalities so that the ontology and the Widget Store share the same set of functionalities.
The third type of metadata is the domain concept describing widgets regarding a knowledge domain they are related to. Widgets can be either generic (e.g. text editor) or targeting specific learning domains (e.g. French language). As some widgets can hardly be described by tool categories or functionalities alone, a categorisation based on learning domains is introduced. The service of DBpediaFootnote 9 is used to allow users the tagging of widgets by semantically unique learning domains supporting them in search for specific tools.
The user interface of the Widget Store allows for searching and filtering widgets according to categories, functionalities, and domain concepts. A list of widgets is listed according to the applied search. Additional filters can be applied regarding the metadata available for the listed widgets. The metadata for each widget is shown in the search result list, that is, category, functionalities, domain concepts, rating, title, and description.
Mashup Recommender
The Mashup Recommender widget (MR) (Fig. 7) can be seen as a filtering system that provides widgets that can be added to the PLE depending on the used template. The MR contains predefined templates, e.g. an SRL template. This template could include the four phases of the SRL process model. If the user selects such a phase, related widgets that support this phase are displayed. For example, if the learner selects the planning phase, calendar widgets, and To-Do-Widgets could be suggested by the MR. For this purpose, the MR uses SRL entities from the ontology. The ontology service is questioned for the respective functionalities of the SRL entities (learning strategies, techniques, and activities) and the widget store returns the associated widgets. Such templates can be created using a special authoring tool.
The MR can be used to provide guidance on different levels and for different stakeholders. A high level of guidance is the preparation of complete predefined PLEs based on a specific template by a teacher or tutor. Later the tutor can share this PLE with her students who can use it or modify it. A lower level of guidance can be provided if the teacher just shares the template with the students, so that they have to create their own PLE. For example, a teacher could select the SRL entities goal setting, resource searching, note taking, and reflecting for a template. Teachers or learners using this template could easily search these SRL entities for widgets and include them in a PLE. In this way the PLE consists of widgets for each SRL entity. Learning strategies are on a higher abstraction level, which results in a greater number of widgets that can be recommended. Learning techniques are on a lower abstraction level, which leads to a smaller number of related widgets that can be recommended. While in the first case the learner gets more widgets recommended and thus less guidance, in the second case the level of guidance is higher because of the smaller number of recommended widgets. For a detailed description of the MR and its technical background, see Nussbaumer et al. (2014).
Activity Recommender
The Learning Activity Recommender guides the learner through the learning process by recommending learning activities related to the SRL process model. The learner is guided by means of a step-by-step approach of how to cope with a problem. In contrast to a direct instruction, the learner can decline to accept learning activities and can choose between alternatives and will not be penalised for varying his learning steps from what is suggested. The Activity Recommender (AR) consists of two widgets, the Activity Recommender widget and the To-Learn List widgets (Fig. 8).
In contrast to collaborative and content-based filtering approaches handling large community-generated data sets, the Activity Recommender is working with data predefined and structured by the educational experts according to the educational approach described in the last section. These experts prepare the recommendations by defining learning strategies, techniques, and matching activities for learning tasks using an authoring tool. The Activity Recommender guides the learners through the learning process by recommending learning activities and assists them to compile a learning plan. In contrast to direct instructions, the learners have a free choice which recommended learning activities they want to perform. When a learner has decided to use a recommended learning strategy, the respective learning activities can be sent from the Activity Recommender to the To-Learn list widget. The To-Learn list widget allows learners to compile an individual learning plan. The widget enables to add, rearrange, delete, and rename recommended learning activities or to add own activities, e.g. reminding them to take a break after a brainstorming session. A learning activity is described with a short summary and a longer descriptive text. Every learning activity has a status that is either not started, started, completed, or cancelled. Moreover, it is possible to specify the learning activities by adding sub-activities on the lower hierarchy levels. Some of the activities are highlighted in red colour, which means there are further recommendations available for this activity. Displaying these recommendations can be triggered by clicking on a highlighted entry. Finally, the entries of the learning plan can be sorted by status, date, or manually.
SRL Text Reader Bundle
The SRL Text Reader Bundle (see Fig. 9) is a predefined widget bundle that supports SRL by providing feedback on the SRL activities. The bundle captures certain SRL activities and displays them in a graphical way to make the user aware about the activities she performs. The main widget is Text Reader where learners can read and annotate texts. These texts and related concepts are defined in a domain model on a backend service. The Self-Evaluation widget allows for relating the assigned tags with concepts from the domain model and to determine the proficiency level for each concept. In this way, the learner evaluates herself regarding her own domain competences. The search widget allows searching additional resources for the domain by searching related tags and concepts. All performed activities are recorded and stored in the user model. The visualisation widget follows an Open Learner Model approach and gives feedback to the learner about her learning process. In addition, the visualisation widget displays the texts that have been annotated and the concepts that have been used for self-evaluation. Guidance is provided by delivering a complete bundle of widgets that support the whole SRL process.
From the user model perspective some different types of information is saved for further usage. The activities a learner performed are saved using the activity schema outlined in the ontology definition in section “Support Strategies”. The concepts coming from a domain model in the background and used for self-evaluation are stored together with the proficiency level as domain competence. The tags related to certain texts are saved as generic information. All this information is used for keeping the user data persistent and visualising the analysis in the Self-Reflection widget.
SRL Monitor
The SRL monitor provides support to develop self-awareness about the performed learning activities. The goal is not only to monitor and visualise the observable actions (as saved in log data), but also to monitor the cognitive and meta-cognitive activities that are not directly measurable. To this end, the measurable actions are mapped to cognitive and meta-cognitive learning activities from the ontology. To be precise, the key actions extracted from the log data analysis (based on an algorithm that clusters the log data) are mapped to elements of the learning ontology. The mapping is partially done by the learner herself, but also supported by an algorithm that takes into account the previous manual assignments. The goal is to make learners aware about their cognitive and meta-cognitive learning activities.
The screenshot displayed in Fig. 10 shows two views of the SRL Monitor. In the first view, the SRL Monitor displays the learner’s captured log data in a sequence. Then the learner can select which learning technique she has actually applied. Based on these selections, reasoning is done regarding the applied learning strategies. Since there are only nine learning strategies, a comprehensive overview of the learner’s behaviour can be given. This overview is graphically shown in the second view of Fig. 10. In this way learners get feedback about their learning behaviour and might rethink their learning process if some learning strategies never appear on the graphical profile.