Engineering technology students’ activities and learning in an electronics laboratory

Laboratories are a staple of engineering education, as is testified by the very large fraction of face-to-face time students spend in laboratories. However, laboratories are an expensive form of instruction in terms of staff as well as equipment. Despite this important role and the high costs, research on their effectiveness is sparse. The research project described in this dissertation studies student learning in a laboratory on first order RC-filters. RC-filters are circuits the students are familiar with from introductory courses they have attended before attending the electronics course and as such serve to introduce typical concepts in electronics including frequency-domain analysis, filters, and Bode plots. Laboratories can be studied from various point of views, including in terms of so-called `effectiveness 1' and `effectiveness 2'. The first type (`effectiveness 1') refers to the relation between what students actually do during a laboratory session and what the teacher intended them to do during the laboratory. The second type (`effectiveness 2') on the other hand refers to the relation between what the students learn from a laboratory session and what the teacher wanted the students to learn from it. As the main interest of this research project is in the students' learning of concepts in laboratory sessions, both types of effectiveness were evaluated from this point of view. 

Before analysing whether and how laboratories contribute to students' conceptual understanding, it is important to verify whether or not learning concepts is indeed a learning goal of laboratories. A first step in the research was therefore to conduct a survey among teachers and their students about the goals of laboratory education in electronics. From this, it became clear that `learning theory' was indeed a major aim of electronics laboratories. 

To gauge students' conceptual understanding, several interviews with students were conducted. From these interviews as well as earlier findings in the literature, a written questionnaire was developed to verify students' understanding of concepts related to RC-filters. This questionnaire then served to probe the conceptual understanding of a wider range of students than interviews allowed, as well as to track student learning by administering it as a pre- and post-lab test. The results of both the conceptual questionnaire and the interviews revealed various problems with student understanding of important concepts such as frequency-domain analysis, filter behaviour and even elementary circuit laws. These problems still persisted in the post-test.  

In addition to using the conceptual questionnaire to study what students learned in the laboratory sessions, the laboratory sessions themselves were audio- and video-taped to analyse what students did and talked about in those lab sessions. To ensure a uniform and consistent analysis, a coding scheme was developed to analyse the recordings. This analysis showed that students spent most of their time gathering measurements and configuring equipment while very little time was spent analysing measurements or discussing underlying theoretical concepts. In addition, the recordings showed that students suffered from cognitive overload (because the topic, the equipment as well as the way measurements were analysed were new) and confirmation bias (because the circuit measured was known in advance). 

Based on the findings of the interviews, conceptual questionnaires and video recordings, a new laboratory session was developed. The design of this new laboratory session was based on ideas from learning by inquiry and variation theory to increase the effectiveness of the laboratory session, while also reducing cognitive load and confirmation bias as much as possible. To decrease the cognitive load during the laboratory session itself, the students could practise the use of equipment by means of a simulator and the processing of measurements at home to prepare for the laboratory. During the laboratory session itself, the students were given a black box of which they had to discover the contents. This approach is inspired by inquiry learning, where the outcome of an experiment and the methodology are not known or fixed in advance. It also eliminates confirmation bias and encourages the students to process their measurement results and think about them already during the laboratory. When they found out what circuit was in their black box, they could trigger a switch that slightly altered the content of the box. They were then asked what had changed in the behaviour of the black box and what had caused this change.

The new black box laboratory was evaluated using the same methods as the original laboratory: by administering the same conceptual questionnaire before and after the lab as well as by recording the laboratory sessions themselves. The recordings indicated that students spent less time gathering measurements and setting up equipment, but more discussing their measurement results and the underlying concepts. The results of the pre- and post-test indicated no change in the students' understanding of filters or signals, however, but did show an increase in knowledge about what Bode plots were. So while the effectiveness 1 clearly increased in the black box laboratory, the effectiveness 2 did not. 

The research project described in this dissertation used a variety of methods (interviews, video analysis, written tests) to verify the effectiveness of laboratory education in a specific electronics laboratory. These methods can be used in other types of laboratories to explore their effectiveness with appropriate adjustments in order to gain a broader insight into learning in laboratories. The project also revealed a difference in increase between effectiveness 1 and 2, raising the question of what the relationship (if any) is between both types of effectiveness. A last aspect that was observed informally, but not studied in depth during the project was the impact of other factors on student learning in laboratories. These factors include, but are not limited to, motivation, the content and style of lectures, student background knowledge, and relationship between pre-existing problems and learning performance.