Abstract
Practical intelligence is often referred to as the ability of a person to solve practical challenges in a given domain. The lack of practical intelligence may be due to the way in which explicit knowledge is valued and subsequently assessed in engineering education, namely via examinations, tests, laboratory reports, and tutorial exercises. The lack of effective assessments on practical intelligence indicates implicit devaluation, which can significantly impair engineering students' ability to acquire practical intelligence. To solve this problem, the authors propose a new method of assessment for measuring practical intelligence acquired by engineering students after performing engineering laboratory classes. The novices-experts approach is used in designing the assessment instruments, based on the behaviors' of novices/experts observed and novices/experts representative work-related situations. The practical intelligence can be measured by calculating the difference between participants' and the experts' ratings; the closer the novices to experts, the higher the practical intelligence acquired.
TopIntroduction
Statistic report by the Ministry of Higher Education in Malaysia on graduates’ employments shows, out of the 184,581 students who graduated in 2012, 24% failed to secure permanent jobs six months after graduation. Out of these, 27.7% are from the technical disciplines which include engineering disciplines (Straits Times, July 2012). The high percentage of unemployed graduates from the technical discipline is alarming as heavy financial costs have been incurred in producing technical graduates. Thus the technical sectors must seek the source and solutions to the current situation.
The engineering education sector in particular, is facing greater challenge in meeting the diverse demands of industries which expect graduate engineers to be well-prepared to provide innovative solutions as technical specialists, system integrators and change agents. A JobStreet survey involving human resource managers in Malaysia on common reasons for turning down job-seekers gave indicators to the problem that need to be resolved by education providers. From this survey 60% percent of the respondents reported that the reason they were forced to turn down job-seekers are poor work skills and weak personality and character.
The unemployed graduates issue is also related to the issue of engineering students’ behavior. Experienced engineers have lamented that engineering graduates do not seem to be aware of the kinds of practical intelligence needed in their workplace (Trevelyan, 2010, 2011). This may result from the way in which explicit knowledge is valued in engineering education: practically all assessments measure explicit knowledge. The lack of emphasis on practical intelligence development is prevalent despite research findings on their relevance to career success in engineering. Findings from numerous empirical studies (Christiansen & Rump, 2009; Eraut, Alderton, Cole, & Senker, 2010; Razali & Trevelyan, 2008a, 2008b, 2009) indicate that the acquisition of practical intelligence in workplace settings and mechatronics laboratory classes is just as important as explicit technical knowledge. This implicit devaluation of practical intelligence could significantly impair engineering students’ ability to acquire and value practical intelligence. Therefore developing new model to include effective assessment could be one way to overcome this problem.
Many engineering educators (Trevelyan & Razali, 2012; Lindsay, 2010) reports on fundamental learning phenomena in conventional hands-on laboratories. To explore this issue, the educators started a project to understand more about the practical learning outcomes from traditional mechatronics laboratory classes. What they found surprised them. They came across a substantial body of research on the notion of ‘practical intelligence’ (PI) that relates to the ability of a person to solve practical issues in a given domain. Psychologists (Bijker, 1995) evolved practical intelligence measurement instruments as part of an extended discipline-wide debate on predicting on-the-job performance of people using results from psychometric tests. Trevelyan & Razali (2010) found that they could apply these techniques to measure significant gains in practical intelligence resulting from participation in hands-on mechatronics laboratory tasks. Practical intelligence is unrelated to students’ results from conventional assessment (examinations, tests, lab reports, tutorial exercises). More interestingly, they found evidence that suggests the possibility that practical intelligence can predict students’ ability to perform fault diagnosis tasks.
Key Terms in this Chapter
Psychometric Test: A questionnaire or survey instrument used to obtain responses from a person in order to assess a psychological attribute of the individual. An intelligence test is one example of a psychometric test. Another common example is the Myers-Briggs personality test.
Incidental Learning: Knowledge gained by experience without the intention to learn anything.
Explicit Knowledge: Knowledge that can be expressed in words.
Critical Thinking: The intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action.
Propositional Knowledge: Explicit statements of truth, for example, water is a liquid.
Survey Instrument: A questionnaire designed to obtain responses from a person in order to obtain data for analysis. Some responses can be quantitative in which case there is a limited number of possible responses, for example ‘yes’ or ‘no’. Other responses can be qualitative in which the person writes a descriptive piece of text, or the interviewer transcribes a verbal descriptive response.
Practical Intelligence: The ability of a person to solve practical issues in a given domain, typically measured with a practical intelligence inventory (a survey instrument or questionnaire). This presents descriptions of typical problem situations, each of which has 10-20 response items. Participants rate the appropriateness of each response item, typically on a Lickert scale, for example 1..7 where 1 means highly inappropriate and 7 means highly appropriate.
Tacit Knowledge: Polanyi (1962) described tacit knowledge, knowledge that we do not know that we know, such as the ability to ride a bicycle.
Research Group (Control and Treatment): In the design of experiments, treatments are applied to experimental units in the treatment group (s). In comparative experiments, members of the complementary group, the control group , receive either no treatment or a standard treatment.
Implicit Learning: Knowledge gained by experience.