## 5 Discussion and Conclusions  
The main research questions in this article are how to conceptualize experiential learning involving sensors and what kinds of learning applications involving sensors already exist or can be designed. In previous chapters, a framework for sensor-based mobile learning environments has been formulated and used to characterize learning activities in several examples involving sensors. In general, [PERSON]'s Experiential Learning Theory presents the learning process as a circle that is divided into four stages: concrete experience (CE), reflective observation (RO), abstract conceptualization (AC) and active experimience. In such a learning process where technology and sensors are involved, the experience were defined to be a (a) technology-mediated learning experience; (b) sensor data augmented learning experience; or (c) collective sensor data augmented learning experience. The examples and scenarios presented in previous chapters show that this classification can be used to describe learning experience in cases where technology and sensor are involved.  
There has been a lot of discussion about what are the skills and competences that will be needed in our society in the future. The core skills and competences mentioned in the literature include thinking and problem-solving skills, learning and innovation skills, communication skills, digital literacy skills and skills for life-management (for example, [52]). Sometimes, these competences are also referred to as twenty first century skills. It is claimed that experiential learning, context information- and sensor data-based learning environments support these core skills and competences. In order to support the claim, the examples of learning experiences augmented with collective sensor data presented above are described using the following skills and competences: learning and innovation skills, digital literacy skills and life-management skills.  
In Table 1, the examples presented in Chapter 4 are characterized using the selected skills and competences. The set of skills and competences used in Table 1 is neither a complete set of twenty first century skills nor a complete synthesis of competences presented in the literature under this title. However, it presents a substantial share of skills and competences commonly referenced in twenty first century learning.  
According to the present study, sensors and sensor networks provide new possibilities for a variety of learning applications. Some of these applications promote twenty first century learning, as such. In addition, the understanding of sensor-based contextual data and the skill to apply these data to everyday activities in learning and life could also be considered an important part of digital literacy and personal life-management in the future.  
The core concepts for analyzing learning in environments involving sensors are based on [PERSON]'s experiential learning and to the concept of a technology-mediated experience. When an experience is influenced by sensor data, it is considered to be a sensor data augmented experience. Finally, collective sensor data augmented experiences involve several individuals and their sensor data, which are combined to produce collective data. The role of technology is to mediate the experience to the community. However, technology-mediated experiences also contribute to the continuum of the experiences and to learning. Learning experiences always have a context, and sensor data may reveal the context to the learner and to the community in such a way that enriches the learning experience or, for example, can lead the learner to what-if problem solving situations, thus contributing to the skills needed in our future societies.