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Recent years have seen an increase in the acceptance and recognition of engineering education research (EER) on a global scale. In particular, over the past ten years, EER has increased in India. Since EER is still in its early stages in India, it is important to comprehend the various EER research methodologies so that the most appropriate ones can be used when carrying out EER-related activities. Three methodologies are used in EER: quantitative, qualitative, and mixed. This paper's goal is to provide a thorough explanation of all the steps used in qualitative research methods for EER, along with relevant examples. Qualitative research is an investigation of a research topic under consideration by collecting non-numerical data to understand perceptions, opinions, experiences or beliefs of individuals or group of individuals. In qualitative research studies, data is collected through interviews, observations, focus group discussions, studying documents, etc. Qualitative research methods are used to fundamentally gain a unique in-depth understanding of a research topic which otherwise is difficult to explore through surveys used in quantitative research. The various steps involved in a qualitative research study typically consist of (1) concentrating on your interests and choosing a research topic, (2) framing research questions to be investigated, (3) conducting a thorough literature review, (4) choosing/creating an appropriate framework to guide the study, (5) designing the research, (6) choosing the research site and research participants, (7) collecting data, (8) analyzing the collected data, (9) documenting significant findings, and (10) publishing results. Qualitative research has many benefits, including the collection of rich data, detailed evaluation of the data, an open-ended research process, the development of specific insights, etc. As a process document to direct themselves when conducting qualitative research projects, this paper will be helpful to beginning engineering education researchers. [ABSTRACT FROM AUTHOR]

This paper presents an instrument designed to assess the Social Problem-Solving Self-Efficacy of freshmen engineering students. This instrument included 34 items and comprised of 5-dimensions: rational problem solving (RPO), positive problem orientation (PPO), avoidance style (AS), negative problem orientation (NPO) and impulsivity or carelessness style (ICS). This instrument was administered in the fall 2019 to freshmen engineering students at a large private southern Indian university. Exploratory factor analysis revealed 4-factors: positive approach towards problems (PAP), AS, NPO and ICS. For these 4-factors, Cronbach's alpha ranged between 0.63 to 0.87. t-test was conducted on the 4-factors to find the differences related to gender, background, and prior experience. For PAP, participants with prior experience reported higher self-efficacy than the participants without experience. For AS and NPO, participants without prior experience reported higher self-efficacy than the participants with experience. However, there were no significant difference on the four factors with respect to gender and background. [ABSTRACT FROM AUTHOR]

In this article, the authors explore and understand what constitutes engineering thinking and whether secondary and higher secondary school curricula in India empower students to make an informed decision regarding engineering as a career choice. To analyse the elements of engineering thinking, the principles of K12 level engineering by t he Na t io nal Aca demy of E nginee ri ng a nd Engineering Habits of Mind (EHoM) by the Royal Academy of Engineering are referred to. The syllabi of the Central Board of Secondary Education (CBSE) and four Indian states (Tamil Nadu, Maharashtra, Andhra Pradesh and Karnataka) are studied, which reveal that CBSE includes only one element of EHoM (creative problem-solving) in higher secondary grade curriculum. The syllabi of four Indian states revealed that the principles identified by the National Academy of Engineering (NAE) are missing in both grades. As an exception, the syllabus of Maharashtra has a creative problem-solving element in class-12 of higher secondary grades. The authors believe that introducing engineering thinking in schools will empower students to choose engineering as a career. [ABSTRACT FROM AUTHOR]

In the recent past, engineering education research (EER) is gaining increasing acceptance and recognition globally. Specifically, EER is growing in India over the last decade. As EER is nascent in India, there is a need to understand the different research methods in EER such that appropriate methods are chosen while conducting EER-related activities. EER involves three methods: quantitative, qualitative, and mixed research methods. The purpose of this paper is to document in detail all the steps followed by specific examples in quantitative research methods when conducting EER. Quantitative research is a systematic investigation of a research topic under consideration by collecting quantifiable data and performing mathematical and statistical manipulations on the collected data to produce findings that add to the existing body of literature. In quantitative research studies, data is collected by sending out online polls, questionnaires, surveys, etc. Quantitative research methods are used to fundamentally quantify different aspects in research-related activities such as attitudes, beliefs, behaviours, opinions, etc. of the samples under study to provide meaningful conclusions with noteworthy implications. The different steps used in a quantitative research study typically include (1) focusing on your interests and finalizing the research topic, (2) framing research questions to be investigated, (3) conducting a thorough literature review, (4) choosing/creating an appropriate framework to guide the study (5) designing the research, (6) selecting the research site and research participants, (7) collecting data by sending out surveys, (8) analysing the collected data, (9) documenting important findings, and (10) publishing results. Quantitative research offers various advantages including reaching a higher sample size, quick data collection, the generalizability of the findings, etc. This paper will be of help to novice engineering education researchers as they can use this paper as a process document to guide themselves when conducting quantitative research projects. [ABSTRACT FROM AUTHOR]

Although researchers agree that student engagement in online courses is a function of time dedicated to course‐related activities, there is little consensus about the best way to quantify the construct. This study introduces a measure for undergraduate engineering students' engagement in online courses using their interactions with their online course learning management system (LMS). Data from 81 courses offered by three fully online, undergraduate engineering degree programs generated a total of 3848 unique student–course combinations (approximately 2.7 million rows of LMS interaction data), to which we applied a five‐step process to calculate a single score representing student LMS engagement. First, we converted the students' LMS interaction data into a set of natural features representing the time they spent per 3‐day period on various course elements, such as quizzes, assignments, discussion forums, and so forth, and how these times changed across the duration of the course. We then used the natural features to derive 216 relative features describing deviations from typical interaction patterns among students in the same course. Next, we conducted association rule mining on a training portion of the data set to generate rules separately describing the behavior of students who completed the course (completers) and those who chose to drop early (leavers). The rules generated were applied to students from the testing portion of the data set to compute the percentage of unique rules met by completers and leavers. Finally, the mathematical difference between the percentages of completer and leaver rules met by each student was found to be the best measure of student engagement. [ABSTRACT FROM AUTHOR]