Introduction to Academic Work Course Book PDF

INTRODUCTION TO ACADEMIC WORK DLBCSIAW01 INTRODUCTION TO ACADEMIC WORK MASTHEAD Publisher: IU Internationale Hochschule GmbH IU International University of Applied Sciences Juri-Gagarin-Ring 152 D-99084 Erfurt Mailing address: Albert-Proeller-Straße 15-19 D-86675 Buchdorf [email protected] www.iu.de DLBCSIAW01 Version No.: 002-2024-0405 N. N. © 2024 IU Internationale Hochschule GmbH This course book is protected by copyright. All rights reserved. This course book may not be reproduced and/or electronically edited, duplicated, or dis- tributed in any kind of form without written permission by the IU Internationale Hoch- schule GmbH. The authors/publishers have identified the authors and sources of all graphics to the best of their abilities. However, if any erroneous information has been provided, please notify us accordingly. 2 TABLE OF CONTENTS INTRODUCTION TO ACADEMIC WORK Introduction Signposts Throughout the Course Book............................................. 8 Basic Reading.................................................................... 9 Further Reading................................................................. 10 Learning Objectives.............................................................. 13 Unit 1 Theory of Science 15 1.1 Introduction to Science and Research.......................................... 16 1.2 Research Paradigms.......................................................... 20 1.3 Research Decisions.......................................................... 22 1.4 Impact of Scientific Paradigms on Research Design.............................. 26 Unit 2 Practical Application of Good Science 29 2.1 Research Ethics.............................................................. 31 2.2 Evidence.................................................................... 33 2.3 Data Protection, Affidavit, and General Legal Information........................ 34 2.4 Spelling and Format......................................................... 37 2.5 Identification and Focus of Research Topics.................................... 38 2.6 Research Question and Outline................................................ 39 Unit 3 Research Methods 45 3.1 Empirical Research........................................................... 46 3.2 Literature Reviews........................................................... 47 3.3 Quantitative Data Collection.................................................. 48 3.4 Qualitative Data Collection................................................... 49 3.5 Mix of Methods.............................................................. 50 3.6 Critique of Methods and Self-Reflection........................................ 51 3 Unit 4 Academic Administration: Structure, Application, and Literature Management 55 4.1 Plagiarism Prevention........................................................ 56 4.2 Database Search............................................................. 58 4.3 Literature Management...................................................... 64 4.4 Citation and Writing Guidelines............................................... 66 4.5 Bibliography................................................................ 73 Unit 5 Academic Work at IU: Written Assignment and Research Essays 79 5.1 Written Assignments and Research Essays at IU................................. 80 Unit 6 Academic Work at IU: Project Reports 85 6.1 The IU Project Report........................................................ 86 Unit 7 Academic Work at IU: Case Studies 91 7.1 The IU Case Study............................................................ 92 Unit 8 Academic Work at IU: The Bachelor Thesis 97 8.1 The Bachelor Thesis at IU..................................................... 98 Unit 9 Academic Work at IU: Oral Assignments 105 9.1 Oral Assignments at IU...................................................... 106 Unit 10 Academic Work at IU: Oral Project Reports 111 10.1 Oral Project Reports at IU................................................... 112 Unit 11 Academic Work at IU: The Colloquium 117 11.1 The Colloquium at IU...................................................... 118 4 Unit 12 Academic Work at IU: Portfolios 121 12.1 Portfolios at IU............................................................ 122 Unit 13 Academic Work at IU: Exams 133 13.1 Exams at IU............................................................... 134 Appendix List of References............................................................... 138 List of Tables and Figures........................................................ 142 5 INTRODUCTION WELCOME SIGNPOSTS THROUGHOUT THE COURSE BOOK This course book contains the core content for this course. Additional learning materials can be found on the learning platform, but this course book should form the basis for your learning. The content of this course book is divided into units, which are divided further into sec- tions. Each section contains only one new key concept to allow you to quickly and effi- ciently add new learning material to your existing knowledge. At the end of each section of the digital course book, you will find self-check questions. These questions are designed to help you check whether you have understood the con- cepts in each section. For all modules with a final exam, you must complete the knowledge tests on the learning platform. You will pass the knowledge test for each unit when you answer at least 80% of the questions correctly. When you have passed the knowledge tests for all the units, the course is considered fin- ished and you will be able to register for the final assessment. Please ensure that you com- plete the evaluation prior to registering for the assessment. Good luck! 8 BASIC READING Bell, J., & Waters, S. (2018). Doing your research project: A guide for first-time researchers (7th ed.). Open University Press McGraw-Hill Education. http://search.ebscohost.com. pxz.iubh.de:8080/login.aspx?direct=true&db=cat05114a&AN=ihb.23294&lang=de&site =eds-live&scope=site Deb, D., Dey, R., & Balas, V. E. (2019). Engineering research methodology: A practical insight for researchers. Springer. http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?di rect=true&db=nlebk&AN=1983807&lang=de&site=eds-live&scope=site Saunders, M., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students (8th ed.). Pearson. http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true& db=cat05114a&AN=ihb.45337&lang=de&site=eds-live&scope=site Veal, A. J. (2018). Research Methods for Leisure and Tourism (5th ed.). Pearson. http://searc h.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=cat05114a&AN=ihb.28 583&lang=de&site=eds-live&scope=site 9 FURTHER READING UNIT 1 Gaus, N. (2017). Selecting research approaches and research designs: a reflective essay. Qualitative Research Journal, 17(2), 99–112. http://search.ebscohost.com.pxz.iubh.de: 8080/login.aspx?direct=true&db=edsemr&AN=edsemr.10.1108.QRJ.07.2016.0041&lan g=de&site=eds-live&scope=site Rehman, A. A., & Alharthi, K. (2016). An Introduction to Research Paradigms. International Journal of Educational Investigations, 3(8), 51–59. Available online UNIT 2 Iskander, J. K., Wolicki, S. B., Leeb, R. T., & Siegel, P. Z. (2018). Successful Scientific Writing and Publishing: A Step-by-Step Approach. Preventing Chronic Disease, 15(E79), 1–6. htt ps://doi.org/10.5888/pcd15.180085http://search.ebscohost.com.pxz.iubh.de:8080/log in.aspx?direct=true&db=ccm&AN=131456567&lang=de&site=eds-live&scope=site Journal of Young Investigators. (2005). Writing scientific manuscripts: a guide for under- graduates. Available online Mantzoukas, S. (2007). A review of evidence-based practice, nursing research and reflec- tion: levelling the hierarchy. Journal of Clinical Nursing, 17(2), 214–223. http://search.e bscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=ccm&AN=105999714&lan g=de&site=eds-live&scope=site UNIT 3 Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26(2), 91–108. htt p://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=asn&AN=4030 7111&lang=de&site=eds-live&scope=site Gülpınar, Ö., & Güçlü, A. G. (2013). How to write a review article? Turkish Journal of Urology, 39(Suppl 1), 44–48. https://doi.org/10.5152/tud.2013.054 UNIT 4 Bramer, W. M., de Jonge, G. B., Rethlefsen, M.L., Mast, F., & Kleijnen, J. (2018). A systematic approach to searching: An efficient and complete method to develop literature searches. Journal of the Medical Library Association, 106(4), 531–541. http://search.ebs cohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=edsdoj&AN=edsdoj.5b9b9a a48cf44c44beb67cbb18fba3e6&lang=de&site=eds-live&scope=site 10 Fenner, M., Scheliga, K., & Bartling, S. (2014). Reference Management. In S. Bartling & S. Friesike (Eds.), Opening Science: The Evolving Guide on How the Internet is Changing Research, Collaboration and Scholarly Publishing (pp. 125–137). Springer International Publishing. https://doi.org/10.1007/978-3-319-00026-8_8http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=edsdob&AN=edsdob.20.500.12854.3198 6&lang=de&site=eds-live&scope=site Ivey, C., & Crum, J. (2018). Choosing the right citation management tool: Endnote, Mende- ley, Refworks, or Zotero. Journal of the Medical Library Association, 106(3), 399–40. Available online Jereb, E., Urh, M., Perc, M., Lämmlein, B., Jerebic, J., Urh, M., Podbregar, I., & Šprajc, P. (2018). Factors influencing plagiarism in higher education: A comparison of German and Slovene students. PLoS ONE, 13(8), 1–16. http://search.ebscohost.com.pxz.iubh.d e:8080/login.aspx?direct=true&db=asn&AN=131195118&lang=de&site=eds-live&scope =site Prusek, O., Mach, J., Gojná, Z., Kozmanová, I., Černikovský, P., Vorel, F., Vorlová, H., Tesaříková, K., Holeček, T., Mach, J., Římanová, R., Hradecký, J., Foltýnek, T., Fontana, J., & Henek Dlabolová, D. (2021). How to Prevent Plagiarism in Student Work. Karoli- num Press. http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db =edsdob&AN=edsdob.20.500.12854.49609.2&lang=de&site=eds-live&scope=site Watson, M. (2020). How to undertake a literature search: a step-by-step guide. British Jour- nal of Nursing, 29(7), 431–435. http://search.ebscohost.com.pxz.iubh.de:8080/login.as px?direct=true&db=ccm&AN=142668427&lang=de&site=eds-live&scope=site UNIT 5-8 Eco, U. (2015). How to write a thesis. MIT Press. http://search.ebscohost.com.pxz.iubh.de:8 080/login.aspx?direct=true&db=nlebk&AN=963778&lang=de&site=eds-live&scope=sit e Iskander, J. K., Wolicki, S. B., Leeb, R. T., & Siegel, P. Z. (2018). Successful Scientific Writing and Publishing: A Step-by-Step Approach. Preventing Chronic Disease, 15(E79), 1–6. ht tps://doi.org/10.5888/pcd15.180085http://search.ebscohost.com.pxz.iubh.de:8080/lo gin.aspx?direct=true&db=ccm&AN=131456567&lang=de&site=eds-live&scope=site Oliver, P. (2012). Succeeding with your literature review: A handbook for students. Open Uni- versity Press. http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true& db=nlebk&AN=435001&lang=de&site=eds-live&scope=site UNIT 9-11 National Conference of State Legislatures. (2017). Tips for making effective PowerPoint pre- sentations. Available online 11 Polonsky, M. J., & Waller, D. S. (2004). Making Oral Presentations: Some Practical Guide- lines and Suggestions. The Marketing Review, 4(4), 431–444. http://search.ebscohost.c om.pxz.iubh.de:8080/login.aspx?direct=true&db=bsu&AN=16669231&lang=de&site=e ds-live&scope=site UNIT 12 Corwin, T. (2003). Electronic portfolios. Campus-Wide Information Systems, 20(1), 32–38. ht tp://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=edsemr&AN =edsemr.10.1108.10650740310455586&lang=de&site=eds-live&scope=site UNIT 13 Fernández-Castillo, A., & Caurcel, M. J. (2015). State test-anxiety, selective attention and concentration in university students. International Journal of Psychology, 50(4), 265– 271. http://search.ebscohost.com.pxz.iubh.de:8080/login.aspx?direct=true&db=bsu& AN=103668248&lang=de&site=eds-live&scope=site 12 LEARNING OBJECTIVES Introduction to Academic Work explains the basics of scientific theory and presents the most important aspects of good scientific practice. The building blocks of fundamental academic knowledge include an introduction to research methods and mechanisms. This introduction into academic work provides an overview of the most important compo- nents of academic writing that the student can practice in real-world lessons. These les- sons then introduce the different types of IU International University of Applied Sciences exams, providing insight into their requirements and implementation. This combination of theoretical principles and practical execution lays the foundation for the future of scientific work. 13 UNIT 1 THEORY OF SCIENCE STUDY GOALS On the completion of this unit, you will have learned... – the essential characteristics of scientific research. – how to distinguish between different fundamental research assumptions. – how to identify core research decisions. 1. THEORY OF SCIENCE Case Study Simon is studying business administration at IU International University of Applied Scien- ces (IU) while also working at zielNET, a small market research company. Four years ago, he successfully completed his training as a marketing and social research specialist at ziel- NET. During that time, he completed a written assignment that focused on how different customer groups formed their opinions. Simon loves getting to the bottom of things, as Goethe’s Faust (1808/2005) says, “To know what holds the world together at its core”. Having a particular interest in analyzing target groups and group behavior is what led him to his current profession. Simon’s supervisor appreciates this analytical quality and often turns to him for advice on how to approach specific consumer groups. Currently, Simon is involved in an important project for zielNET: analyzing the recent prod- uct failure of a long-time major customer. Despite the fact that zielNET invested six months in the product’s relaunch, customers still appear to have no interest in purchasing it. Simon now tries to address this issue empirically in his current course. What does it actually mean to work scientifically? He is trying to remember models and theories that dealt with consumer decisions and buying behavior of certain target groups and that could be helpful for investigating the issue at hand. 1.1 Introduction to Science and Research This section begins with some key reflections on research and addresses scientific theory. This may seem tedious and complicated at first, but it should quickly become clear that the underlying structures of science have a major influence on our everyday lives. Addi- tionally, analytical tools will be provided to enable a critical examination of results of future research projects and their fundamental assumptions. Case Study: Observation, Reflection, and Reasoning The following situation serves as a starting point for further discussion. Thousands of years ago, a hunter and gatherer was out collecting branches of wood. On the way back to his village, he stumbled and the branches fell to the ground. Understandably, his initial reaction was one of annoyance. However, he began to compare this situation with other previous experiences and realized that things actually fall down again and again, but noth- ing ever falls up. He continued to reflect and realized that this applies to all the things around him: tree branches, animals, stones, fruit, etc. Even the leaves that he recently col- lected for the shelter floor had fallen down, albeit more slowly. Some leaves were even blown away by the wind, an event which he had never observed with stones. At this point 16 he realized that everything he collects can fall down—even if the speed of doing so differs —but nothing has the ability to fall up. He now wonders if other members of his tribe are aware of this, or if they know of anything that falls up. Without being able to provide answers to these questions, one could proceed as follows: First, the tribal elder could be questioned along with some other tribal members about their experiences with falling objects. However, their opinions may diverge. For example, the tribal elder could remind him that the souls of the deceased ascend to the gods, i.e., fall up, not down. Other tribal members might claim to have seen leaves fly up due to a particularly strong wind. While there might be a few who swear that there are objects that do fall upward, on the whole, there is agreement that the tendency is for most things to fall down, with estimates of speed varying greatly. Although these assessments point us in the right direction, many questions remain unan- swered. It is now necessary to consider how the whole phenomenon could be subjected to a more detailed investigation. The Science Council (2009) defines science as “the pursuit and application of knowledge and understanding of the natural and social world following a systematic methodology based on evidence”. Science can also be defined as, “[t]he intellectual and practical activ- ity encompassing the systemic study of the structure and behavior of the physical and nat- ural world through observation and experiment” (Lexico.com, 2019a). Science usually means the process of research and, more precisely, scientific research. The following definition applies: “Scientific research is conducted within the rules and conventions of science” (Veal, 2018, p. 6). This means that scientific research is a systematic, rule-based process used to gain knowl- edge. In the case above, the initial observation (branches fall down) cannot be considered to be at the level of scientific research yet; however, following a systematic and estab- lished process brings us closer to this goal. Based on scientific concepts broadly accepted today, such as the fact that gravity exists, one can find out a lot about the subject of gravity. In fact, due to the ubiquitous availabil- ity of information, some of these explanatory approaches and theories can now be regar- ded as established knowledge. Therefore, one would certainly agree that the explanation of gravity can be regarded as true. But is that explanation incontrovertible? At this point, one can refer again to the tribal elder talking about the ascending souls of the deceased. Can people be absolutely sure that such a thing does not exist? The question of whether something is considered true depends on the basic assumptions of our worldview. It is known, for example, that witness statements after accidents or crimes are often unre- liable because different witnesses can have completely different recall about the event itself. One person swears that he heard three gun shots, while another person at the scene says she heard only one gun shot. The vehicle fleeing the scene that caused the accident was a blue SUV, says one person, while to someone else it appeared to be a black station wagon. Each of these individuals is absolutely convinced that they are telling the truth. 17 Indeed, there are many situations that people accept as true and at the same time remain questionable, depending on certain basic assumptions people share. Here are a few exam- ples. Example: True blue When someone refers to a blue house, there is an unspoken assumption that the house they are referring to is painted blue. However, for a person who is color-blind, this descrip- tion is not their truth. Here it is assumed that the color-blind person is wrong, because they cannot recognize the color blue. But is this really the case? Do people think of this person as ill because they cannot see color? What would happen if color-blind people were actually the dominant group and everyone else was suffering from a “color vision” mutation? What if suddenly most people could no longer recognize colors and agreed that the few remaining people who could see them were themselves ill? Then the blue house would suddenly be something that does not even exist, since for the color-blind, it would be a shade of gray. The description of a blue house would no longer be true; rather, the truth—as generally shared knowledge—would be that the house is gray. On the subject of “what is truth”, the following cognitive optical illusion serves as an illus- tration: Figure 1: Rubin’s Vase Source: Becker-Carus & Wendt, 2017, p. 124. In the image of Rubin’s vase, is it true that two faces are depicted or is it true that a vase is depicted? Or are both things true? This question of fact should be differentiated from the question of what the observer sees. On closer examination, the central scientific frame- work of observation also proves to be questionable. 18 Example: Global poverty According to the United Nations Department of Economic and Social Affairs (2019), extreme poverty has risen in the United States; in Europe there has been an overall decline, but the number of poor people is still higher than prior to the 2008 financial crisis. In many countries, the gap between rich and poor continues to widen. For this purposes, a “relative concept” of poverty is used when discussing this topic. Relative poverty is “deter- mined by income distribution over a given population and defined according to societal norms” (Open Education Sociology Dictionary, 2020). According to the relative concept of poverty, someone is regarded as poor if that person earns less than 50 percent of the median income in the society they live in. This seems plausible and, according to the spe- cific definition given, is one true way of measuring poverty. At this point, it should neither be discussed whether this concept of poverty makes sense, nor it should be denied that poverty is lamented in our societies. What is important here is that this particular definition of poverty creates truths that are politically relevant and can also be questioned. If in a country with 15 percent poverty, for example, all salaries were doubled from one day to the next, the country would still have a deplorable poverty level of 15 percent. Mathematically this is correct, but is it true? This up for discussion. The examples of color perception and poverty are intended to raise awareness to the fact that scientific research produces results that are generally regarded as true. However, this truth is always based on certain assumptions that must be considered when trying to understand and classify the results achieved. Statistics play a major role in societal and political contexts; however, it is often very difficult to evaluate the validity of “hard facts” because information is lacking. Given all these complex requirements, it seems quite challenging to become a successfull scholar; especially, when thinking of big names such as Einstein, Galileo Galilei, Marie Curie, and Maria Goeppert Mayer. However, research often means going “two steps for- ward, one step back”—a slow and steady process that allows even novice researchers to be successful. Scientific research produces findings that can be regarded as true in the sense that researchers’ assumptions are known and shared. Nutritional recommendations over the last 60 years, for example, have been based on scientific research. Meat diets, carbohy- drate diets, low-carb programs, interval fasting, therapeutic fasting, moderate alcohol consumption, no alcohol consumption, the Mayo diet, etc., all came about because of sci- entific recommendations and findings that resulted in facts being recognized as “truth”. However, scientific findings are also opportunities for critique. Criticism is an extremely important part of the scientific research process because it gives rise to new ideas for future research projects. During this course you will acquire the tools to understand research, critically question it, and develop your own research approaches. With regard to the relevance of research, it can be stated that research findings are not only used to explain existing conditions, but also partly to predict future developments. Here are some examples of scientific questions: 19 Why is Apple in a position to market mobile phones and computers at substantially higher prices than its competitors while offering essentially the same performance? How does international milk consumption affect theCO2 balance of the environment and thus climate change? How can agile leadership in medium-sized production companies influence efficiency and productivity? These examples convey a first impression of how complex open questions can be, includ- ing all their conceivable sub-aspects, in the broad field of science and research. 1.2 Research Paradigms Research, and the way in which scientific research is approached, has a lot to do with underlying assumptions. There is a need to review the steps that prior studies have taken and to also think about the basic assumptions of the own research project. These basic assumptions are also referred to in the literature as paradigms or, more precisely, as research paradigms. Research paradigms are the most fundamental convictions from which knowledge is gained in the research process (Guba & Lincoln, 1994; Saunders et al., 2019, pp. 138–151). Depending on the research question, different positions can be taken: Scenarios A and B will be used for comparison: A. How does the acceleration from 0 to 100 km/h of a vehicle change when special gaso- line is used as fuel as compared to the use of normal gasoline? B. How do leaders of social organizations evaluate their own ethical approach when deter- mining an organization-wide ethical orientation, according to Swiss economist Peter Ulrich? When having a look at both questions, it is immediately apparent that each question requires a different scientific approach to find the answer. In scenario A, an experiment will most likely be carried out in which the same vehicle will be refueled once with normal gasoline and once with special gasoline, the exact same acceleration conditions will be utilized, and a time measurement will be carried out. In addition, the testing conditions will be reproduced as exactly as possible to generate a reliable conclusion, i.e., weather conditions and subsurface conditions will be replicated. In scenario B, attitudes of a particular group of people—leaders in social organizations— need to be investigated. The organizations themselves can vary greatly, as can the atti- tudes about ethics; the latter is based strongly on the values held by the survey respond- ents. The standardization of the research process tends to be more difficult than in sce- nario A as there are many influences on the respondents and on the survey situation that are difficult to standardize and control. 20 These two research scenarios illustrate different underlying scientific assumptions— research paradigms. In order to understand the path to knowledge for both scenarios, four questions are typically asked (Guba & Lincoln, 1994, pp. 107–108; Saunders et al., 2019, pp. 144–151): Ontology: What is truth? What can a person say is true? Epistemology: What can humans know? Methodology: What instruments can be used to gain knowledge? Influence of the researcher: To what extent does the researcher influence the research results? When looking at these four questions, the differences between scenarios A and B become clear. For scenario A, it can be assumed that there must be an unambiguous result for the acceleration behavior of the different types of gas (ontology) and that this result is also exactly measurable and reproducible (epistemology). If the test arrangements are identi- cal for both gas options, the results are not open for interpretation and can therefore be regarded as objectively true. Methodically, one will almost certainly conduct an experi- ment in which one leaves all conditions as similar as possible and only changes the gas used (methodology). In this respect, the influence of the researcher is kept out of the research process as much as possible (influence of the researcher). In scenario B, while talking to leaders of organizations will definitely deliver relevant insights, the “truth” here will manifest itself in interpretation-related tendencies (ontol- ogy). Therefore, it will be difficult to arrive at a definitive and unequivocal conclusion (epistemology). In methodological terms, an experiment does not seem to apply to this scenario, rather one would most likely use open questions so that the managers can express themselves freely (methodology). In such a survey, influences of the researcher are hard to eliminate because factors such as the type of question, mood, preferences, and dislikes can be important influencing factors (influence of the researcher). The result is not a measurable value as in scenario A, but rather an assessment based on interpreta- tion. Scenario A is presumably based on an “explanatory research paradigm” (Saunders et al., 2019, p. 144–147; Gubrium, 2012, p. 417). In the literature, this paradigm is also called “positivism” and includes different versions. However, it is not necessary to go into more detail on this here. Scenario B is based on an “understanding research paradigm” (Guba & Lincoln, 1994, pp. 110–116; Gubrium, 2012, p. 417), often referred to as “constructivism”, of which again there are different versions but will not be expanded upon here. The following table gives an overview of the most important points for each research paradigm. Table 1: Fundamental Research Paradigms Paradigm Explanatory Paradigm Understanding Paradigm Ontology: A person can make statements Reality occurs in humans What is truth? What can one say about reality (objects, living through experiences, attitudes, is true? creatures, etc., in the world). and surroundings. 21 Paradigm Explanatory Paradigm Understanding Paradigm Epistemology: Objectifiable conditions: Generally subjective insights What can humans know? Insights and findings are meas- and findings arise through inter- urable and also exist for multi- actions and interpretation pro- ple people. cesses. Methodology: Experimental methods, standar- Interpretative methods, qualita- What instruments can be used dized methods, quantitative tive methods to gain knowledge? methods Influence of the Researcher: Influence is excluded as much as Subjectivity of the researchers: To what extent does the possible. They are involved in the researcher influence the research process because no research results? interpretation would be possible without them. Source: Created on behalf of IU (2020). Thus, an explanatory research paradigm searches for universally valid laws by subjecting theories or assumptions to a test in order to either confirm (verify) or refute (falsify) their universality. Since reality here is regarded as non-individual—i.e., independent of the indi- vidual—one tries to exclude the subjectivity of the researcher as much as possible. In con- trast, the understanding research paradigm assumes that reality is always constructed by the individual and arises through interpretation. In this respect, the subjectivity of the researcher is an integral part of the research process. An understanding research paradigm often motivates research fields in which little or no theoretical approaches exist. Each research paradigm has a different impact on the further development of research strategies. It is important to note that no paradigm is considered “better” or “superior”, rather each research paradigm has its relevance in different fields of research, often even complementing each other. 1.3 Research Decisions Research paradigms determine the way research is conducted. Furthermore, research questions often already allow to make conclusions about the underlying assumptions. For a research question to be asked, the central ideas for carrying out the investigation must be formulated in advance. There are several research decisions to be considered which is also referred to as research design. The following decisions, among others, have to be made (Bazeley, 2004, p. 141; Bell & Waters, 2018, pp. 23–46; Creswell & Creswell, 2018, pp. 3–21): type of research strategy type of scientific reasoning type of data type of research to be carried out 22 Type of Research Strategy This research decision is aimed at the question and choice of methodology, of whether research should be quantitative or qualitative. Research is primarily about collecting, ana- lyzing, and interpreting data, data that sometimes can be very different in nature. Quanti- tative research aims at results that can be expressed in data, e.g., sales figures or average Quantitative research length of stay in health care facilities (Saunders et al., 2019, pp. 176–178). In quantitative This type of research gathers numerical data research, a mathematically comprehensible, mathematically “correct” result is obtained and analyzes it via mathe- and thus the research arrives at a statement whose accuracy — assuming mathematically matical methods. precise procedures were followed — cannot be refuted. However, the interpretative aspect of quantitative research is often “hidden” in the translation or reduction of complex terms into numerical scales (e.g., the term “quality of life” in clinical studies on patients at the end of their lives). In quantitative research, representativeness is also important, i.e., the extent to which the result obtained for a sample can be generalized to the population as a whole. A good example is election research, which typically involves 1,000 or 2,000 people in an attempt to obtain a representative picture of the general population (i.e., the entire electorate). In quantitative studies, relatively large samples are often used to test previ- ously established hypotheses, and the resulting data are summarized. Qualitative research uses, amongst others, text-based data that must be interpreted, i.e., Qualitative research qualitative research examines the individual case (Saunders et al., 2019, pp. 179–180). In This type of research gathers non-numerical qualitative research, the result is a conclusion obtained from an interpretative process. data and analyzes it Because interpretation is by nature subjective, the results of such research are up for through meaning inter- debate and their validity can be questioned. Therefore, qualitative research typically does pretation. not aim at representativeness. Rather, specific participants are selected, with the expecta- tion that they can provide in-depth insights into the subject being researched. Due to the very complex process of data collection and analysis, it is usually only possible to work with small samples when performing qualitative research. For example, researchers might be interested in the reasons why people do not vote in an election. In order to explore deeper motives here, interviews with a few participants are conducted where they explain in depth why they do not vote in elections. The aim is to obtain useful and rich informa- tion. In addition, one might want to ask why job turnover in certain industries is higher than in others. Here, interviews capture motives and underlying causes and are discussed in confidentiality; the information gathered from these interviews might otherwise not have been obtained with a standardized questionnaire. Quantitative research is sometimes said to mean that mathematical accuracy does not automatically mean “correct” with regard to research questions. This is how, for example, mistakes are made confusing correlation with causality (Reed, 2005 as cited in Saunders et al., 2019, p. 148). A light-hearted example can be that the number of human births per year in Germany and the number of storks (which are said to fly the babies to the expecting parents’ homes) living in Germany have both declined considerably over the last 70 years. If the biology department was not paying attention, they might immediately conclude that there are fewer children in Germany today because there are also fewer baby-bring- ing storks. Here, the numbers actually correlate, but the causality is not given. Correlation If two phenomena are related in some way or have some sort of con- nection, they are consid- ered correlated. 23 Causality Qualitative research is often assumed to be pure storytelling, and, in this respect, one If one phenomenon is often speaks of anecdotal evidence. This means that something is recognized as a found to affect or influ- ence another, they are research result because it has been said often enough. This is associated with the accusa- said to have a causal rela- tion that scientists using qualitative research only find out what they assume (Diefenbach, tionship. 2009). If, for example, female participants in middle management of a company are asked about the “glass ceiling” (the phenomenon in which women are discriminated against when seeking leadership positions), it is more likely than not that the interviewees actually confirm the existence of the glass ceiling in their statements. Here the result is expected—the knowledge gain remains small because it is obvious that the researchers asked questions for which they already knew the answers. It is therefore particularly important in qualitative research to reflect on one's own research process and to analyze it critically. Looking at these two very different research strategies—quantitative and qualitative research designs—the ongoing scientific debate about which approach is “better” is easily understood (Bell & Waters, 2018, pp. 23–27). In fact, one can argue that there is no “better approach” per se, but that either research strategy is ideal depending on the particular research project. For example, for large samples, a research object that can be easily quantified, and the requirement for generalizability (i.e., representativeness) of the results would definitively lead to quantitative research. The desire to gain deeper insights into a little-explored field with more text-based data makes qualitative research design seem reasonable. Researching employee satisfaction in a company would probably be better determined quantitatively, whereas conflict and trauma within teams would be investiga- ted more qualitatively. The sciences and humanities understand that these approaches do not contradict each other, but can also be used together in a process called triangulation. Types of Scientific Reasoning The second research decision concerns scientific reasoning. Here a distinction between induction and deduction is drawn, both closely linked to underlying research parameters and the decision for a qualitative or quantitative research strategy (Saunders et al., 2019, pp. 152–155). Induction Induction first looks at an individual case or a few cases and draws general conclusions This is a process by which (Saunders et al., 2019, pp. 154–155; Veal, 2018, pp. 48–51; Sheppard, 2004, pp. 49–52). If individual cases are used to derive a generalization. one has no knowledge of car brands and their specific characteristics, but a Ferrari passes you on the road, you might conclude that Ferraris are always very fast cars. Although you may be familiar with this car maker, it could have been pure coincidence and all other Fer- raris are totally underpowered, slow vehicles. Induction is therefore often used to develop a theory from a few single cases, which one could test further, with more observations, so as to achieve a more solid conclusion. Deduction Deduction is the opposite of induction and moves from general conclusions to individual This is a process by which cases. Typically, a theory is used, and this theory is tested on a case-by-case basis (Saun- a general premise is applied to specific, indi- ders et al., 2019, pp. 152–154; Veal, 2018, pp. 48–51; Sheppard, 2004, pp. 49–52). If the vidual cases. theory states that all Ferraris are particularly fast cars, then it follows that a Ferrari stand- ing on the street in a residential area must be a fast car. To be on the safe side, the theory 24 (all Ferraris are fast cars) would be investigated by testing the Ferrari. If the car proves to be fast, the theory would be confirmed; if the Ferrari is slow for any reason, the theory would be refuted or falsified. Quantitative research usually uses deduction. Induction is more common in qualitative research; however, there are times when deductive approaches are taken. Type of Data When it comes to the basic decisions of research, it is important to consider the different types of data. A distinction is made between primary and secondary data (Veal, 2018, p. Primary and secondary 52; Rea & Parker, 2014, pp. 4–5). Primary data are generated for the purpose of the current data Primary data are gener- investigation. Therefore, when interviews are conducted, the interview records are consid- ated for the investigation, ered primary data. The same applies with regard to participants’ individual answers on while secondary data standardized questionnaires. The primary use of such data is for the researcher who col- were originally collected for a purpose outside the lected the data. research project. Secondary data are data originally collected for a different purpose, which is then used for a new and different investigation (Saunders et al., 2019, pp. 316–318; Tantawi, 2021). For example, if a market research institute uses economic data to draw an absolute compari- son between two countries, and a different research group uses the same data to analyze whether there is a correlation between religious affiliations and economic data of various countries, the data are known as secondary data. Type of Research to Be Carried Out How research is implemented is also part of the fundamental decisions of research. Here, a distinction is made between experimental and non-experimental investigations (Cres- Experimental investiga- well & Creswell, 2018, pp. 11–13). One possibility of non-experimental investigation is the tions These types of investiga- “field-research”. This type of research is carried out “in real life” (Arrington, 2021), e.g., tions take place in a plan- interviews with managers at their workplace. It is particularly important for observations ned environment. to study participants’ behavior in real context and then analyze it. Experimental research means creating a controlled environment in which investigations will be carried out. The advantage here is that the environment is controlled and any interference can be ruled out (Stoica, 2021). In marketing, for example, laboratory supermarkets (i.e., those that only simulate the shopping situation) are used to investigate whether and how customers can be encouraged to buy certain products. The fact that a shelf with sweets is typically found at the cash register is probably the result of experimental studies in which it was established that children like to “motivate” their parents to buy another chocolate bar while waiting in the checkout line. The research decisions mentioned here represent some of the cornerstones of research upon which data collection and analysis can be built and planned. 25 1.4 Impact of Scientific Paradigms on Research Design The essential assumptions about research have a direct impact on research design (Saun- ders et al., 2019, pp. 128–132; 172–175). Since research paradigms allow conclusions to be drawn about the underlying assumptions of research, this results in a logically stringent sequence of research design. Research is a process that one follows, much like a formula. Accordingly, it must be possible to establish, critically reflect upon, and justify the research approach. The following graphic provides information on the connection between research para- digms and research design. Figure 2: Connections between Basic Research Decisions Source: Created on behalf of IU (2020). The figure illustrates that with the formulation of the research question and the research object, a large part of the research decisions have already been made, or at least a specific research strategy appears probable. The following two examples provide further informa- tion. Example: Introducing rent control 26 The government plans to introduce new legislation to limit rent increases (rent control) and institutional landlords will be questioned about their attitude to such regulation and the associated challenges. The research question is formulated: How do institutional landlords assess the introduction of rent control in relation to their busi- ness model? From this question one would lean more toward an understanding research paradigm, since it is clearly a question of personal assessment. This offers a qualitative research strategy that focuses on the analysis of text-based data. The form of scientific reasoning may tend to be more inductive, as a few cases are considered and theory is generated rather than tested. If experts from rental companies should be interviewed, primary data would be generated. If the survey were to take place at the workplace of the interviewees, it would be a non-experimental research design. Example: Kids and chocolate The goal is to discover whether parents who shop with their children buy more of the chocolate bars prominently displayed at supermarket checkouts than adults who shop alone. The following research question is formulated for this purpose: How does buying behavior change with regard to chocolate bars offered at supermarket check- outs when adults go shopping with their children? Here one can assume a rather explanatory paradigm, since number-based data are most likely used and a representative research result is the goal. In this respect, a quantitative research strategy can be assumed and thus also a deductive—in this case theory-tested— form of scientific reasoning. If video recordings of a laboratory supermarket in which a research institute originally observed the buyers in relation to a different issue were used, secondary data would now be employed when using the recording for this research. The setting corresponds to an experimental research design. Research should be structured in categories so that the readers seeking results can under- stand and comprehend the process and outcomes. This still leaves room for criticism and discussion, both of which are highly important as this is the base upon which scientific progress is built. SUMMARY Science and research differ to a considerable extent from the everyday knowledge and experience of an individual. In this unit, scientific theo- ries have been introduced in order to provide initial insight into availa- ble research paradigms. These theories serve as a starting point for sci- entists and academics to make important research decisions and to choose which research design works best for their empirical and/or 27 experimental inquiry. With the help of practical examples and scenarios, an application-oriented introduction to this often very abstract and challenging subject is provided. 28 UNIT 2 PRACTICAL APPLICATION OF GOOD SCIENCE STUDY GOALS On completion of this unit, you will have learned … – about the importance of ethics in research. – how to verify and evaluate the quality of scientific studies and research. – when using a non-disclosure agreement and affidavit is required. – what role spelling and structure have in academic writing. – how to identify a topic and continuously narrow the research question. – how to develop a research question and use it to scaffold academic work. 2. PRACTICAL APPLICATION OF GOOD SCIENCE Case Study Maike is an ambitious employee in a large company. In order to advance further in the company, she has decided to go back to school part-time to pursue a bachelor degree. While the content of her studies interests her, she quickly realizes that she has difficulties with academic work. The first written assignment is already torturous for Maike, making her uneasy about her bachelor thesis, which requires an empirical study. She will need to conduct an investigation and either develop or test hypotheses, depending on which research paradigm she chooses. Eventually Maike decides to test a hypothesis empirically for her second research essay, which is due soon. She chooses a qualitative approach without knowing whether it is suitable for her research question. Ascertaining the research design and data collection become quite complicated, and, after a third failed interview, she is about to give up altogether. The pressure is mounting and the due date is fast approaching. In her distress, she invents the missing interviews and lets a fellow student— Joana—do most of the analysis. To thank Joana for her help, she invites her to a popular music concert. Maike submits her essay on time and states in the affidavit that she carried out the research independently without the help of others—only making mention of her acquaintance Joana, in the acknowledgments. Despite the weak scientific basis of the work, she is compelled by her professor to publish the results in an IU paper, making them available to the broader scientific community. Maike now has moral dilemma because she manipulated her data. She is afraid that a larger number of critical readers will increase the possibility that someone will discover her deception, especially when she learns that her work will be scanned by plagiarism software. In the specific case of Maike, many questions can be asked with regard to good scientific practice. Why is honesty important, not only morally, but even existentially, in scientific research? What drives researchers to manipulate or falsify results? How can an outsider judge whether a study is trustworthy and qualitatively reliable? How can students avoid such early defeat and demotivation with academic writing? It is important to show students how to apply and implement good scientific practice from the very beginning. The following content on how to implement good scientific applica- tion should be practiced with all IU-specific examinations, and in particular with data pro- tection, affidavits, correct spelling and formatting, and topic identification or differentia- tion. 30 2.1 Research Ethics When it comes to ethics in research, many people likely think of crimes committed against groups of people in the name of scientific progress. Throughout the history of modern sci- ence, people who did not have the power or the knowledge to defend themselves were exploited in experiments in the name of scientific or medical progress in a way that today are considered immoral. Especially in medicine, which starts with the ethos of healing people or at least alleviating suffering, such trials are a particular outrage, as with the infa- mous Tuskegee study in Alabama, USA from 1932 to 1972 (Benedek, 1978). This study investigated the natural course of syphilis; however, the African-American male patients were neither told what they were suffering from nor given access to medication, causing many to die in agony. Ethical issues naturally arise in other disciplines as well. In the economic and social scien- ces, for example, protecting study participants’ data and personal information is becom- ing both ever more important and challenging. As gradually the private and the public with increasing social media use is mixed, it is becoming very difficult for researchers to effectively protect study participants from the misuse of data collected (Canadian Insti- tutes of Health Research et al., 2018; Saunders et al., 2019, p. 259). However, ethical issues need to be taken into account right from the beginning of any research project and need to be present with every step of a work that claims to be scien- tific (Saunders et al., 2019, p. 252). Why? Postulating scientific results means claiming truth. The concept of truth—also scientific truth—is highly complex and books written on this subject fill the library shelves of all major universities (Ghins, 2017). Put simply, relia- bility and accessibility of scientific results form a basis for the work of all scientists world- wide—the scientific community. Thus, it is essential that scholars respect academic hon- esty and can be trusted. It is this honesty that encompasses all the steps necessary for scientific insight and discovery. From topic selection to publication, incentives and pres- sure can become so high that researchers could find themselves guided by motives other than those grounded in the pursuit of science and truth. Robert King Merton, an American sociologist and science theorist, formulated ethical norms that are still regarded as the foundation for science (as a system or institution), even as they are constantly adapted and redefined over time (Bucchi, 2015). According to Merton, these standards are also referred to as CUDOS principles (Merton, CUDOS principles 1973) and include the following. These principles describe the four basic ethical norms in scientific 1. Communism: Scientific knowledge does not belong to the individual researcher, but research. rather to the scientific community and society as a whole, which carries and facilitates all research. Scientific results can only be recognized when published and made avail- able to the community. 2. Universalism: Scientific statements are valid regardless of the social class, religion, race, or other characteristics of the researcher. Scientists should only be judged on the basis of their scientific performance. 31 3. Disinterestedness: Scientists and scientific institutions may only act for the sake of scientific progress and not for personal reasons (e.g., career, political opportunity). 4. Organized skepticism: Scientific results should not simply be believed, but must be reviewed by the researcher and by the scientific community; only then can scientific truth be affirmed. This control must be anchored in scientific institutions and in the broader scientific system. Robert Merton (1973) postulated these norms not so much for the individual researcher’s morality—it was clear to him that scientists are people just like everyone else—but rather for the institution or system of science, which, in his opinion, cannot exist without these foundational norms. It is not difficult to imagine in how many places these principles are challenged today: authorship in the digital age; the increased competitive pressure among researchers to publish quickly and frequently (how, for example, can the scientific community still accu- rately check the flood of publications?); and influential persons and institutions (“gate keepers”; Bucchi, 2015) who determine who gets what position or which research grants, etc. The list of breaking points for honest research goes on and on. After a few blatant, public cases of scientific misconduct, almost all major national and international research societies, universities, and other scientific institutions have created for themselves a repu- table set of standards for scientific work, its review, and implementation (for the U.S. and Canada, as well as some international guidelines, see the compilation of The University of British Columbia, 2019 or Saunders et al., 2019, pp. 254–255). Saunders et al. (2019, pp. 257–259) considered ten ethicals principles, that occur across many different approaches for research: integrity, fairness and open-mindedness of the researcher respect for others avoidance of harm (non-maleficence) privacy of those taking part voluntary nature of participation and right to withdraw informed consent of those taking part ensuring confidentiality of data and maintenance of anonymity of those taking part responsibility in the analysis of data and reporting of findings compliance in the management of data ensuring the safety of the researcher One could perhaps formulate a brief summary of the international efforts toward scientific honesty in this way: anyone who produces sloppy work, deliberately conceals, falsifies, or invents results, or does not appreciate employees, destroys the possibility of science. If the scientific community and its institutions cannot establish rules, verify compliance, and enforce them, not only will the reputation of science be damaged, but science itself will no longer have a chance to pursue the discovery of universal truths. 32 2.2 Evidence After exploring ethics in research, it is necessary to examine the role of evidence in science (Elsevier Author Services, n.d.). However, first, a few words about the term “evidence”. Evi- dence is a much-discussed term in philosophy and science (philosophers such as Ludwig Wittgenstein and Edmund Husserl, for example, could be mentioned here). Generally speaking, evidence is “the available body of facts or information indicating whether a belief or proposition is true or valid” (Lexico.com, 2019b). It is important to mention that not every study meets the standards of good science (Elsevier Author Service, n.d.). Studies show differences regarding the quality of research design, implementation, and review. So, how can one determine whether or not an experi- ment is reliable and qualitatively acceptable? This question may surprise some, as it is generally assumed that scientific studies always provide new and reliable results. Unfortu- nately, this is not always the case. This makes it all the more important to subject studies to a review. In order to assess whether a study provides reliable data, it is important to determine the reason why the experiment was conducted and what question it investiga- ted. This may sound trivial, but it is crucial in order to determine whether the study is able to thoroughly answer the research question. Subsequently, the methodology of the study should be considered, in particular whether the methodology used was appropriate to answer the research question, whether it was carried out properly, and whether there were systemic errors (bias) that could distort the results. The following questions can help to evaluate studies: Is the study design suitable to answering the research question? How were the participants approached and selected? Who or what was included/excluded and why? Did the researchers describe the procedure and the results completely and comprehen- sibly so that the study could be repeated and reviewed? Were the samples large enough and the number of experiments frequent enough to answer the research question? Was the study conducted long enough? How many participants or testing arrangements/experiments were eliminated or unsuc- cessful during the study and why? How many participants or experiments could no longer be investigated during the period post-study (for follow up) and why? Was the study conducted by an independent institution or by the private sector? Are the samples and number of tests performed representative and sufficient to estab- lish conclusive evidence? In addition to this fundamental assessment and evaluation of a research study, there are levels of evidence, or classifications of evidence, that provide information on whether research is of high quality and whether its results can be scientifically communicated. 33 “Evidence class” is a term mainly used in evidence-based medicine to describe and cate- gorize the formal and substantive quality of a study. It describes a hierarchy of evidence. The scientific significance is thus evaluated with the help of evidence classes, or levels of evidence (Elsevier Author Services, n.d.). The five levels of evidence hierarchy are (Man- tzoukas, 2007, p. 217): Meta-analysis Level 1: Evidence from at least one meta-analysis of RCTs (Randomized Controlled This method tries to stat- Trails) istically summarize early research projects on a Level 2: Evidence from at least one well-Conducted RCT certain topic. It is a sum- Level 3: Evidence from controlled research without randomization mary of many sources of Level 4: Evidence based on research without experimental study primary data. Level 5: Evidence based on opinions/reports of recognized authorities Randomization In this procedure, partici- pants are assigned to dif- Definition of evidence levels or classes may vary between organizations and differ ferent groups in an unplanned manner. between specialties, according to the clinical question being asked (Murad et al., 2016; Burns, 2011). 2.3 Data Protection, Affidavit, and General Legal Information In many research areas, working with personal data is inevitable, whether it is a written data record, video recordings, or images. All of these possible empirical sources and infor- mation are subject to data protection regulations. Those working in scientific research must therefore know and comply with the applicable regulations, consistently implement- ing them in their scientific practice (Saunders et al., 2019, p. 276). In the following, aspects of data protection that must be taken into account in academic writing will be explored. Collection of Personal Data within the Scope of Surveys If the survey requires personal information, i.e., if the respondents can be identified, vari- ous data protection measures must be put in place (Saunders et al., 2019, pp. 276–278). This is also the case even if a name or other personal data are not identifiable and are replaced or redacted, making it very difficult to identify the person in question; in such a case, one speaks of pseudonymity. Regardless, pseudonymous surveys must be treated just like surveys containing personal data. Examples of such guidelines include data minimization. Collecting too much personal data should be avoided. (What data are absolutely required for the purpose of the survey and how do they have to be for the research purpose?). legality. The collection and processing of personal data may have a legal basis. If there is no legal permission for the processing of data, the consent of the interviewee must be obtained. 34 deletion of data. Personal data must be deleted as soon as they are no longer needed. For scientific surveys, the data must be kept for ten years, even if the survey is part of an examination. At the end of the ten-year period, the data must be deleted. When disseminating or publishing the results of scientific surveys, all personal informa- tion should be removed beforehand. For example, if a student conducts a survey that is part of a research essay, the survey participant data should be pseudonymized before the essay is submitted. This means that names must be replaced by pseudonyms or com- pletely redacted. No names should be visible so as to ensure the anonymity of the inter- viewee. If no personal data is collected and/or used in a survey, no data protection consent has to be obtained. Personal data is not collected or used if the data is completely anonymous, i.e., if it is not possible to draw conclusions about the person or an attribution to a person. Copyright Laws The use of graphics and photos in academic work can be tricky, especially when figuring out who owns the graphic or photo in question and if consent is given for its use in text and on other platforms, such as on social media. In order to use such images, one must follow the law of the country. The regulations for using photographs in Germany, for example, are clear: all photographs are protected by copyright (§ 72 UrhG). The following provides clarification on the usage of graphics and images when submitting an academic paper in Germany, respectively on a university located in Germany. Use of images (without personal reference) Images, graphics, and maps that have been previously published (e.g., available online) may only be used if the work references them. This means that there must be a a relation- ship between the image and the text (Section 51 No. 1 UrhG). In addition, the creator of the image needs to be cited. The Citation Guidelines show how to correctly cite images. Questions: 1. Is this image necessary? 2. Does the idea remain valid without the image? 3. If a trademark (image, text, water mark, etc.) is depicted in the image in question, the following applies: In principle, trademarks (logos) are also protected by copyright. It must not appear that there is a relationship between the trademark proprietor and the user if there is actually none. A copyright infringement of a trademark is excluded if it is only an “insignificant accessory” in the overall image. The decisive factor for this is that the object protected by copyright and trademark law cannot be the main design of the image (e.g., a company sign in the image of a large shopping street). Icons are also protected by copyright. If icons are used, the creator of the icon should also be named, unless the icon is in the public domain. 35 Concerning media, Microsoft grants a license for its products such as Word and Power- Point in projects and documents to copy, distribute, and display media elements (images, clip art, animations, sounds, music, video clips, templates, and other types of content) that are part of the software. The content contained in those programs may therefore be used for handouts and presentations provided that they are reproduced for a limited number of participants and not used commercially. This also applies to research essays. However, the use solely for illustration purposes is not permitted and always requires the consent of the copyright holder. Images from social media are also protected by copyright. Pictures of people as well as of landscapes from social media platforms are copyrighted and may only be used with per- mission. In the case of pictures in which people are depicted, in addition to the consent of the author/photographer, the people depicted in the image themselves must also consent to their image being used. Such consent shall not be subject to any condition and must contain detailed information on the data used, the purpose of the data used, the storage period of the data, and whether disclosure to third parties is planned. Due to the large amount of information contained in such consent, it is imperative that it be obtained in writing. Screenshots are also treated mostly like images where many of the same considerations apply. It must serve to clarify the text and cannot be used simply as an “insignificant accessory”. Screenshots of websites and videos are to be treated like image citations. In addition to the image citation, one should obtain the consent of the author or person depicted. Non-Disclosure Agreements In order to protect data and information when pursuing scientific work, there is the option to use a non-disclosure agreement. This is particularly helpful if a scientific paper is writ- ten in cooperation with an external cooperation partner or with a company. Each study can be provided with a non-disclosure or confidentiality agreement. The latter stipulates that the work—without the express consent of the company and the author—will not be made available to third parties, with the exception of the supervising lecturers and author- ized members of the audit committee. The non-disclosure agreement prohibits publica- tion for a specific period of time in an effort to protect sensitive data and research results. At the same time, the scientifically necessary publication of research results can be partly delayed or completely prevented (if the results do not appear optimal), which repeatedly fuels criticism of privately financed research. Therefore, a compromise must always be found between the interests of the company and the interests of the university or the sci- entific institution and community. Violation of a non-disclosure agreement may even result in criminal prosecution. Affidavit An affidavit must be included in every academic work. With this declaration, the author confirms that the work is independent and was not produced with outside help or through the use of outside intellectual property. It is also confirmed that no sources other than those stated were used. The affidavit must be included in the work. It is not submitted as a 36 separate document but forms the last page of the written elaboration (after the annexes). A missing or unsigned affidavit leads to failure of the examination. Unlike many other uni- versities, the declaration at IU is filed electronically before submission. The declaration does not have to be included in the work itself (except for the thesis—further information under Information Thesis in General in myCampus). EXAMPLE AFFIDAVIT I hereby swear that I have done this work independently and without the use of outside help. The sources and tools I used are clearly marked as such and refer- enced at each instance in the text. This work has not yet been submitted in the same or a similar form to any other examining authority. I agree that the work will be checked for plagiarism with the help of a plagiarism detection service. ______________________ Signature 2.4 Spelling and Format A research paper must meet certain formal criteria which serve to ensure legibility, trans- parency, understanding, and clarity (Saunders et al., 2019, pp. 731–739). The excessive use of personal pronouns as “I” and “we” should be avoided in academic writing (Saunders et al., 2019, p. 737). If the researcher takes an active part in the research process, moderate use of personal pronouns could be reasonable. Language should be gender-neutral, non- binary and not discriminating. More information is found in the IU guidelines for gender- inclusive/sensitive language available in myCampus. The spelling (orthography) of each work should be adapted to meet the current standard and must be applied consistently. Spelling and typing errors should be avoided by reading the work several times, and one can even use third-party reviewers, before submission. Students whose native language is different from the one used in the examination should have their work proofread by a trained native user for the review of language, style, and understanding. The paper is preceded by a title page on which the author (complete with name, postal address, email address, and student number), corresponding event (course, lecturer, semester, and title), and topic and type of work (written assignment, research essay, bach- elor thesis, etc.) are noted. Apart from the title page, all pages must be numbered. The pages before the body of the text (e.g., title page, table of contents, list of tables and abbreviations) should be num- bered in Roman capital letters (I, II, III, IV, etc.), with the page number not appearing on page I (title page). The pages of the text part are numbered with Arabic numbers (1, 2, 3, 37 etc.), beginning with page 1. This is usually the bullet point “1 Introduction”. These page numbers are continued to the end, i.e., also through the appendix. The desired position of the page numbers is centered at the end of the page. Further form specifications can be found in the Exam Guide in myCampus for every type of examination. Ideally, illustrations and tables should be created by the author; previously created graph- ics and images should only be used when absolutely necessary. Images, sound, and video material are subject to copyright and must be identified by cita- tions. Rules for correct citations are found in the general citation guidelines. 2.5 Identification and Focus of Research Topics Before a topic for a scientific paper is decided on and research is started, one should check whether there are certain requirements for that topic area. This applies to all types of aca- demic work. The following questions should be answered “yes” if the topic is chosen freely. Is the subject interesting to me? Can I imagine dealing with the topic intensively for a while? Do I have previous knowledge of the chosen topic? Is the topic of interest important for my further studies and career goals? Does the topic meet the requirements in terms of scope? Topics which may prove unsuitable include those that have been extensively covered (“trending”) and for which there is a wealth of existing literature. represent a strong personal connection, such that scientific discussion and objectivity might become difficult. are still explorative, i.e., for which there is little or no literature available. require the use of sources that are difficult to find or completely unavailable. require the use of sources that are too demanding technically or linguistically (foreign languages). require the use of methods that are not mastered or are unavailable within the given framework. are too abstract, making a practical scientific approach difficult. require elaborate empirical approaches. It is not always easy to answer these questions. For example, whether a topic is extensively researched (or not sufficiently researched) and unsuitable for one's own research work, does not necessarily become apparent after the initial literature search. It is also not always easy to recognize which methods are most suitable for dealing with a topic (Saun- 38 ders et al., 2019, pp. 26–29). Ideally, interesting topics and questions arise continuously throughout the studies. It would makes sense to solidify topic identification and avoid abstractions. Once the working title of the topic is named, the research question to be answered is derived from it (Saunders et al., 2019, p. 42). Depending on the scope of the scientific work, it is also common to formulate two or three research questions related to a topic. These questions help narrow the topic and serve as a common thread throughout the work, and also help with the preparation of the outline. These are examples of poor titles: Leadership in the 21st Century Work 4.0 Digitization in the World of Work These are examples of better titles: The Model of Transformational Leadership in the Energy Industry: Innovation or Trend? Influence of Digitalization in the Service Industry Using the Example of Call Center Soft- ware in the Insurance Industry The Effect of Digitalization on the Travel Behavior of Generation Z—An Overview of Cur- rent Applications in the Tourism Industry Using thematic boundaries and constraints can help to determine which aspects should be addressed, which should not, and why. The following example considerations can be used as criteria to narrow the topic: time geography institutions groups of people sources people or authors aspects of a particular discipline theoretical approaches or explanatory concepts theoretical or explanatory approaches according to experts specific, selected aspects 2.6 Research Question and Outline The research question is an integral part of the outline of a scientific work and is embed- ded in the introduction (Saunders et al., 2019, pp. 714–715). The entire outline must follow a common thread, which develops according to the research question being asked. The following image is that of a funnel. The research question in this case is the funnel (with built-in filter), which decides the classification points and facts to be included. Everything 39 that can be processed within the outline of the work and contributes to the assessment of the research question must be included. The outline should demonstrate how the research questions is executed. It must reflect a logical development of the work as well as provide an overview of it. Figure 3: Funnel Function of a Research Question Source: Created on behalf of IU (2020). Examples of research questions include the following: What influence does a manager's leadership style have on employee health? Which evidence-based models are available to application-oriented research on healthy leadership in companies? What research needs arise from the current state of research on healthy leadership? These examples of research questions could all be chosen and developed under the title “Leadership and Health—A Challenge for the Mechanical Engineering Sector”. Outline In the outline, all outline points are listed, if necessary with sub-points. If a subdivision of an outline point is necessary, it must contain at least two sub-points. Table 2: Structure of a Scientific Outline Poor Better 1. Introduction 1. Introduction 1.1 Problem Statement 1.1 Problem Statement 2. Theoretical Foundation 1.2 Objectives and Research Questions 1.3 Structure of the Work 40 Poor Better 2. Theoretical Foundation Source: Created on behalf of IU (2020). As a rule, the work should be divided into a maximum of three section levels (1. Main Heading, 1.1 Section, 1.1.1 Subsection). The sections and subsections must be identical in title and numbering as those mentioned in the text. Because section headings, and the corresponding page numbers, often change during the course of writing, it is advisable to work with corresponding font formats (Heading 1, 2, etc.) from the beginning and create an automated table of contents. The following parts occur in every scientific paper: table of contents (outline with page numbers), text part (consisting of introduction, body and conclusion), bibliography. Other indexes, such as list of figures, list of tables, and list of abbreviations, help the read- ership to find pertinent additional information. The lists of tables and figures as well as the list of abbreviations are listed in the front part of the paper, i.e., between the table of contents and the text part. A list of tables must be listed for three or more tables and a list of figures for three or more figures. Another optional part is the appendix. It serves to present information that is too detailed for the text part, but important for its understand- ing. This can be the original copy of a survey, large tables, or scanned materials and tran- scripts of in-depth interviews. Each appendix must be labeled as an “Appendix” with an appropriate label. For example: Appendix A, Appendix B, etc. Appendix pages are num- bered but are not included in the specified page count of an examination paper. Each appendix should be referenced in the paper. Only the individual sections in the text of the paper are numbered in the outline; the other outline components of the paper, such as the table of figures or bibliography, are indica- ted without numbering. The following basic outline must be taken into account for the text part of a paper (Saunders et al., 2019, p. 714): introduction body (with theoretical background/literature review, methods, findings/results and dis- cussion) conclusion While it is common to include “introduction” and “conclusion” as chapter titles, for the body of text you need to choose chapter titles that are suited for your specific research topic. However, it is important to internalize the basic structure of a scientific paper. Espe- cially the chapters, possibly with their subchapters, in the body must usually be adapted to the specific content. However, it is important to internalize the basic structure of a sci- entific paper. 41 In the introduction, the research question, objective, problem statement, and structure of the work are described, and relevant and interesting facts are provided. It is here that you want to take a look at what might motivate the reader to continue reading (Saunders et al., 2019, pp. 714–715). The theoretical background serves to classify the entire topic and research question into a scientific, evidence-based research context. It is important to present existing knowledge and its relevance to the research question (state of current research) (Saunders et al., 2019, p. 715). In this context, the stringing together of term definitions should be avoided. Therefore, instead of devoting an entire subsection to the definition of terms, these are explained the first time they are mentioned in the text. Table 3: Structure of a Scientific Outline Poor Better 2. Theoretical Foundation 2. Theoretical Foundation 2.1 Definition of Terms 2.1 Health in the Context of Work 2.2 Health in the Context of Work 2.2 Leadership as an Influencing Factor on Health in the Workplace 2.3 Healthy Leadership 2.3 Transformational Leadership as a Model Source: Created on behalf of IU (2020). The method, or research design, describes the how and why in an academic work. In the methods section, the decision to use a certain methodology is explained in more detail. The advantages and disadvantages of the chosen method must be critically considered and discussed (method criticism) (Saunders et al., 2019, p. 717). In this part of the paper, the choosen method and its specific steps are described; e.g., if a systematic literature search was conducted or which empirical process was chosen (qualitative or quantitative). In the findings/results section, the own results, which were generated with the applied method, are presented neutrally, i.e., without evaluation and interpretation. In literature- based work, the results of the literature review are presented. If empirical methods are used, the results of the empirical investigation are presented in this part (Saunders et al., 2019, p. 718). The discussion serves as the final reflection and comparison of the findings against the background of the current state of research, and, where appropriate, political or social developments. Once again, one must reiterate the conclusions to the research question in a relevant and lively way. It is also possible here to describe a model for best practice or to provide recommendations for further action. The identification of further research can also be part of this discussion (Saunders et al., 2019, pp. 718–719). Finally, the conclusion summarizes the entire paper and may also include the subjective opinion of the author (Saunders et al., 2019, pp. 719–720). 42 SUMMARY Good scientific practice places many demands on the author of a scien- tific work. This unit provides a complex profile of the requirements that students are advised to start dealing with at the beginning of their stud- ies to achieve systematic success. Thus, questions of scientific integrity are not only important with regard to the recognition of one's work, but are also prerequisites for science. This is one of the reasons why affida- vits are required for scientific papers. Furthermore, when doing research and writing scientific papers, the examination of data protection and copyright laws is relevant. However, pragmatic guidelines on the structure, form, and outline of a scientific work must also be understood in terms of their form and scope. 43 UNIT 3 RESEARCH METHODS STUDY GOALS On completion of this unit, you will have learned... – the difference between data collection and data analysis. – the essential characteristics of quantitative methods. – the essential characteristics of qualitative methods. – how to explain the quality criteria of research. 3. RESEARCH METHODS Case Study It's a week before the parliamentary elections. Simon and Maike are very interested in pol- itics and world affairs, and both have been politically engaged for years, albeit with differ- ent convictions and political orientations. This makes such political and historical events exciting for them both—not to mention the rich discussions. One week before the big elec- tion, they watched a political debate on television. Directly after the end of the broadcast, a large opinion research institute conducted a survey on party preference (“If elections happened today, which party would you vote for?”). The moderator explains that 1,000 representative participants were surveyed by phone, and the result of the survey will be announced on the next show. According to Simon, “facts”, as presented by the opinion research institute, are unclear and imprecise in many respects and leave much room for interpretation. He explains to Maike that he can hardly believe that the representative sample of 1,000 people accurately reflects the electorate. He is curious on how the sample was selected and the ratios for gender, age ranges, and educational backgrounds. From his own professional experience, he knows how difficult it can be to reach target groups for opinion research. In addition, Simon raises other questions: Were both voters and non-voters really questioned here? How meaningful is such a hypothetical question in the context of a quantitative survey? Would it have made more sense to supplement the survey with an open question on the reasons, i.e., to combine quantitative with qualitative methods? These many questions result in Simon and Maike having an in-depth discussion on empirical research and the associated instruments that lasts long into the night. Seeing how close one's own life is to application-oriented research is quite exciting. 3.1 Empirical Research When doing research, a wide variety of methods are used (Veal, 2018, p. 132). Depending on the research objective and the underlying research paradigm, qualitative methods or quantitative methods can be used (Saunders et al., 2019, pp. 175–178). It is also possible to choose a mixture of qualitative and quantitative approaches, often referred to as meth- odological triangulation (Saunders et al., 2019, pp. 181–184). Since qualitative and quanti- tative research methods have specific advantages and disadvantages, triangulation often serves to compensate for the disadvantages of the respective methodology and should thus lead to a more meaningful research result. When considering the different methodological approaches, it is important to distinguish between data collection and data analysis (Saunders et al., 2019, pp. 176–180, Veal, 2018, p. 47). Data collection has the purpose of generating the necessary data. Data analysis aims to evaluate the available data, which can then be interpreted accordingly. Since the various research methods have both advantages and disadvantages, it is important to 46 think about the quality of an investigation. For this purpose, scientific quality criteria are used, which differ according to the type of research (Saunders et al., 2019, pp. 213–219). These quality criteria not only point to the research quality achieved, but also show the extent to which researchers are able to critically reflect on their own approach. When thinking about the opinion poll discussed above, it is obvious that quantitative research was carried out because the result is based on figures and shows percentages. Moreover, they used a representative sample, although no details are presented that allow to assess the degree of representativeness. The survey was conducted by phone, although it is not known whether landlines, mobile numbers, or both, were included. Furthermore, data analysis has been carried out in a simple statistical way—also referred to as descrip- tive statistics. With regard to research quality, it could be noted that in the phone surveys the interviewer could have an influence on the results through his or her way of speaking or questioning. For some participants it might be embarrassing to reveal their political preference in a phone survey. Finally, the question could be raised as to whether calling late on a Sunday evening might falsify the results, especially since it remains unclear whether or not only landlines and/or mobile numbers were called. With landlines, for example, the problem is that only a few young people still have them, and that it is more likely that they are out on a Sunday evening rather than at home in front of the TV. A criti- cal attitude toward research questions and their implementation is an essential prerequi- site for good empirical research. 3.2 Literature Reviews Not all academic papers present findings from empirical fi

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