As an instrument for measuring thought processes, the Cognitive Reflection Test (CRT) has been widely used in a number of studies [1-3]. Unfortunately, as an instrument, CRT exhibited a number of problems. First, the CRT consisting of 3 items more closely resembles intelligence tests that measure thinking ability, and not individual thought patterns. Second, the CRT does not adequately reflect the attributes of a comprehensive thought process because all CRT items are numerically based and measure the same aspects. Good instruments reflect the characteristics of the attributes tobe measured [4-6]. Third, the data generated from the CRT

is in the form of right or wrong answers, which are nominal or ordinal. Such data quality has limitations to be used in statistical analysis, because it is not applicable to an additional calculation operation or ratio scale data [7, 8], as a result, inferential statistical analysis that is more advanced cannot be applied. Fourth, the CRT results proved to be influenced by respondents' familiarity with the questions [9-11]. That is, if the respondent has worked on the problem and already knows the logic of the problem, the CRT is no longer valid and effective for measuring the thought process. Fifth, the results of validity tests against CRTs are less encouraging, only valid for measuring reflective thinking and not intuitive [12] and their validity is low when repeated testing is carried out [1].

Many attempts have been made to overcome these weaknesses, for example, by Cheng and Janssen [11] and Thomson [10], who tried to compile a new item that they call CRT-2. However, it seems that these efforts cannot significantly eliminate the limitations of the methods. They will face problems that are more or less the same as seen in the first CRT. Therefore, the development of new instruments to measure thinking patterns becomes an urgent requirement. The instrument was developed based on dual-processing theory, namely system 1 and system 2 [13, 14], which were then linked and explored with neuroscience [15-18]. According to the dual-processing theory, it is assumed that system 1 is related to the limbic system, while system 2 is related to the neocortex.

Neuroscientists also discovered the fact that the behavior displayed by humans has a neuro basis in brain structure [16, 19]. Peters explained that the frontal area of the brain functions to make decisions based on rational reasons, including weighing, analyzing, and considering an action in depth from the good-bad and profit-loss aspects. People who think logically and deeply use a lot of frontal areas in their thought processes. In contrast to the frontal area, the limbic area functions to respond instinctively to emotional stimuli that tend to be rushed, impulsive, and not infrequently destructive. People, who respond to problems emotionally without thinking long, prejudice without data, and draw conclusions speculatively, use a lot of limbic areas in the thought process.

In psychology, the problem is actually not new, but has been studied since the 1970-1980s. Later this theme became phenomenal after Kahneman conducted an in-depth study of cognitive biases in decision making, especially relative to the economic behaviour of individuals [13]. Kahneman argues that to make a decision, humans generally use experience bias, and do not use their ratios optimally, and tend to discourage short-term interests. Consequently, many actions, as a result of the decision making process, are counterproductive and less effective in achieving goals. Kahneman uses the terms thinking fast and slow, which are the concepts derived from system 1 and system 2 [14-20]. Thinking fast is characterized by the decision-making process that is emotional, intuitive, automatic, lacks in-depth consideration, and is difficult to control over instinctive desires. Meanwhile, thinking slow is characterized by rational decision making, requires in-depth consideration, is relatively flexible, and adaptive to rules.

If an individual is accustomed to using intuitive thinking patterns in making decisions, then in the long run, his or her mind cannot function optimally and critical thinking habits will not be developed. Finally, individuals disregard the reference to understanding problems clearly, including solving problems in life. This situation is not only unfavorable but also counterproductive to progress. In the reality of everyday life, indications of the use of intuitive thinking patterns still occur in many societies. For example, many people are exposed to fraud under the guise of investment plans , which obviously makes no sense. The abundance of information that is often called “big data” is apparently not directly proportional to the intelligence of individuals in acting and making decisions [21, 22]. What emerges is precisely the prevailing irrationality marked by the loss of rational reasoning and the lack of awareness of the importance of the verification process before coming to conclusions. People become rushed, spontaneous, instant, and are impulsive without thinking about the truth and dignity that underly it.

For education, the thinking patterns are closely related to the process and learning outcomes [23-25]. Learning is not just meant as an effort to get an academic score, but rather as an effort to build a civilization that educates life [26, 27]. Information as a source of learning can come from classroom activities such as teaching materials, explanations from lecturers, and communication between students through a discussion process, and can also spread via the public cyberspace such as the internet and social media. The research on thinking patterns becomes urgent in the current post-truth era, when people tend to accept truth based on their emotions and beliefs rather than based on the proven facts [21, 22]. The truth seems not to be determined by data and facts, but by individual perceptions and beliefs. If the facts are in line with their beliefs, they are convinced of the truth without their verification [28]. This condition is amplified by VUCA (Volatility, Uncertainty, Complexity, Ambiguity).

Thus, the thinking patterns become a crucial problem in building civilization and are a fundamental problem in education. The question is how to identify thinking patterns that meet psychometric eligibility [6, 29]. So far, two common instruments are used by researchers, namely the Cognitive Reflection Test – CRT [9, 30] and self-reports such as Thinking Styles Inventory – TSI [31, 32]. The first instrument is more like an intelligence test that measures an individual's cognitive abilities, rather than revealing thinking patterns preferred by the individual or habits of thinking [1]. While the second instrument may identify a person's thinking preferences, but after being tested on a broader scale, many of the items are underrated. Out of a total of 104 items, only 32 have psychometric eligibility [33]. It seems that the theoretical basis used, namely mental self-government, which considers the brain mechanism as a government organization less relevant. More or less the same situation happened in the Rational Experiential Inventory - REI [20], the development of which is itself based on Cognitive Experiential Self-Theory (CEST). Thus, the development of thinking pattern instruments is still open to concern.

Identifying thinking patterns is an important part of the process of improving thinking performance in education. Unfortunately, until now, there is no instrument that can be used to identify patterns of thinking adequately. Therefore, developing instruments that include psychometric requirements is a necessity task. This research aims to develop a thinking pattern instrument that meets psychometric requirements, namely validity and reliability. If the purpose of this research could be achieved, as a result, a new model that adequately describes the thinking patterns in students could be implemented by the researcher and lectures to improve student education. As educators, we will not be able to improve students' thinking if we are unable to find the relevant thinking patterns. Error thinking, in turn, will have an impact on errors in behavior. Thus, the results of this research are very useful for making an intelligent civilization in a constructive and progressive manner.

Through an in-depth examination process, starting from exploratory factor analysis, confirmatory factor analysis, and SEM, this research succeeded in developing a scale of thinking patterns that meets psychometric criteria. The IRS has 20 items (see appendix) that are bipolar-related, consisting of 5 factors, namely: effort, evaluation, tempo, response, and result. These factors reflect the attributes of thinking as demanded by a good instrument [4-6]. We identified a number of characteristics such as efforts in searching and finding solutions, speed of responding to stimulus, and evaluation of stimulus, and we have also found new aspects in the thinking process that have been overlooked so far, namely regarding “results” as a dependent variable of thinking patterns. The intuitive thinking patterns often produce dissatisfaction, loss, and even the feeling of regret; while reflective thinking has a greater chance of producing satisfaction [17].

IRS has a loading factor of 0.40 - 0.80 with an eigenvalue greater than 1 and explains 52.57% variance, and has a reliability of 0.71. IRS as a psychometric indicator of thinking process is equivalent to REI which consists of 10 items. REI has a loading factor of 0.59 - 0.79 with an eigenvalue greater than 1 and explains 48.2% of variance, with reliability of 0.72 and 0.73 [20]. The development of IRS is not only based on statistical analysis that is commonly used in the preparation of scala such as inter-item correlations, regression analysis, and Cronbach's Alpha reliability [34], but it includes a more sophisticated approach, namely using SEM. By using SEM, the conceptual relations model between variables can be seen simultaneously [7, 37]. The test results show a little difference between the conceptual model and research observed data with CFI= 0.96 and RMSEA= 0.07.

IRS is an alternative instrument to measure a person's cognitive pattern. It is known that to measure cognition, CRT is a commonly used instrument [1, 9, 30], although it has many weaknesses [12]. A number of researchers have identified CRT’s weaknesses, such as it is more like intelligence tests, in the form of numerical calculations, and there is an aspect of familiarity that affects the validity of the results. Thus, the results of our investigation are in agreement with some previous studies [1, 12]. Our results have proven that IRS is an effective predictor of academic performance. The relationship between thinking patterns and academic performance is a necessity [24, 38] and that is supported by our finding as well. Thereby, the thinking pattern should directly relate to the learning achievements in students.

What are the implications of this research? Identification of thinking patterns by using good instruments becomes urgent in the education and training of individuals, regarding decision-making. It has been reported that humans do not have an encouraging track record in making decisions and tend to be biased in thinking [39]. Many initial decisions become inappropriate after in-depth evaluation of the facts and truths. For instance, it is described that 44% of advocates do not recommend their children to choose the same careers, 40% of executives leave their jobs in the first 18 months, and more than half of the teachers leave their jobs in the first 4 years [40]. In our recent investigation, 13% of students made the wrong choice of the education program. The highest rate occurred in the faculty of social sciences by 26%, followed by the faculty of language and arts by 18%. Regarding the choice of profession, 63% of the students said they would choose a non-educational profession and only 37% chose the teaching profession [41]. Many facts reported in the literature affirm that individual decision making tends to be inaccurate and often leads to regret. The dominated role of limbic system in the process of the intuitive thinking is incontestable.

We designed IRS analysis and used it to describe the thinking pattern in students population. This is to be considered that the problem of thinking is not only the monopoly of the education community [38, 42], but it exists in almost in all areas of life including politics, economics, and government bureaucracy. Thus, in the future, other researchers could implement similar methods and procedures for identification of “typical thinking patterns” in other population groups and compare them. It is possible that there could be a difference in structure on thinking patterns in various professionals .

This research has answered a number of problems that are of concern to researchers related to the use of CRT as an instrument to measure thinking models. This research has succeeded in developing a scale of thought patterns which we later call IRS. The instrument has a conceptual relationship structure consisting of 5 factors with a loading factor of 0.40 - 0.80. The five factors explain 52.57% of the total variance. From the reliability testing, IRS has a Cronbach’s Alpha of 0.71. IRS is correlated and is a significant predictor of students’ academic performance. In terms of the conceptual relationship model, the IRS has been tested using SEM and proven to be fit with empirical data. In connection with the results of this research, it is recommended that the IRS can be used as an alternative to measure individual thinking tendencies. As an instrument, the IRS needs to be further tested by involving other relevant variables, such as socioeconomic level, education level, parenting, leadership patterns, and successful performance.

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The authors declare no conflict of interest, financial or otherwise.