Abstract:

STEM is the educational paradigm that focuses on obtaining by learners the interdisciplinary knowledge and skills so needed for our life and work in the 21st century. The STEM skills are “a combination of the ability to produce scientific knowledge, supported by mathematical skills, in order to design and build (engineer) technological and scientific products or services”.

In this paper, we introduce the term Integrated STEM-driven CS skills (shortly ISTEM-CS skills) and refer to it as a compound of four top-level components:
(1) Learning & Innovation skills;
(2) Scientific and Mathematical Thinking skills;
(3) Computation Thinking skills and
(4) Technological and Engineering Thinking skills.

Each top-level component consists of a set of lower-level skills and relationships among them as defined by the devised model that we have developed using ideas taken from the recent (selected) Web of science papers. Therefore, the aim is to propose a model for the practical use that combines skills categories with skills measuring approaches in order to define skills level. We distinguish among the prognostic (expected) skills that a given Learning Object (LO) might or could carry when delivered and the factual skills that a learner is able to achieve after completion of the learning session using this LO. We define any of these by levels (features) L1, L2, L3, L4, and L5 according to the Ordinary Likert’s scale (L1 is the weakest and L5 is the strongest) evaluated by the relevant metrics from the defined list of possible metrics. The list includes cognitive skills metrics based on the revised Bloom’s taxonomy, creativity and innovation skills metrics, communication and collaboration skills metrics. The levels of prognostic skills are identified at the LO design phase typically by experts or by the CS teacher. We argue that this information should be a part of the metadata description of this LO for its targeted search. The factual level of skills is obtained during the assessment after the real world task solving. This process may require one or more LOs.

The teacher has to rely on:
(i) the essence of LO and its prognostic skills;
(ii) his /her knowledge and observation; and
(iii) the model based on existing metrics and awareness of relationships among skills categories (sub-categories) and metrics types.

The contribution of the paper is a systematised definition of the relationships among skills categories and possible metrics in terms of the proposed model and automatic generation of the template of the model for the practical use. We support this contribution with a case study in STEM-driven Computer Science (CS) education using ARDUINO microcontroller for the real world tasks solving.

Keywords:

STEM, integrated STEM skills, scientific thinking, computational thinking, engineering and technological thinking, learning and innovation skills.