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Evaluation Of Search Tools for Finding Reliable Information in SoftwareEngineering Reports

Amara Boateng

Student at The City College of New York

Writing for Engineering ENGL 21007

ACKNOWLEDGEMENT

I thank our course instructor, Jonathan McVey, for giving us the opportunity to conduct this labactivity and hone our research skills. Thanks for your support in navigating the search engines,databases and tools used in this study. I am grateful to our fellow students for aiding me inreviewing the lab reports. Finally, I acknowledge search engines, databases, tools and articlesused as resources and support. Without that this research would not have been possible.

ABSTRACT

This lab report aims to investigate the effectiveness of search engines and databases in improving information literacy in software engineering. The lab activity involves collecting 30 search results from Google, Google Scholar, and engineering databases and evaluating them based on five criteria: relevancy, authority, accessibility, currency, and expectancy. The data gathered from the evaluations are analyzed using Excel for logical and analytical purposes. Lab work is a key part of the Writing for Engineering course and plays a significant role in assisting students in strengthening their research, critical thinking, and information literacy skills. The findings of this lab report can supply insights into the best practices for conducting efficient and effective searches in software engineering.

Keywords: software engineering, lab work, techniques, tools, research, effectiveness, information literacy, search engines, databases, relevancy, authority, accessibility, currency, bias, limitations, critical thinking, credibility, targeted results.

INTRODUCTION

Software engineering is an essential field that has a significant impact on many aspects ofmodern life. The application of software engineering principles, techniques, and tools is crucial in creating high-quality software products. However, the current understanding of the best practices for software engineering still has certain gaps that need to be addressed. There is a needfor more research to figure out the effectiveness of various software engineering approaches. This lab work aims to bridge this gap by providing students with hands-on experience in applying software engineering principles and methods and evaluating their effectiveness in practice.

This lab activity is designed for a class of 28 students and is a part of the second semesterWriting for Engineering course. The focus is on information literacy, which includes looking for relevant information using a choice of search engines and a wide range of engineering databases.The lab work aims to improve students’ ability to observe and have logical analysis, critical thinking, and research skills. Analyzing and reviewing search engine results are essential aspects of this lab assignment.

Prior research, the effect of software engineering practices on software systems has been the subject of numerous research. Effective software testing strategies were found to be among the most efficient methods for enhancing software quality, according to a study of controlled trials in software engineering (Kitchenham, S., & Charters, S., 2007). Also, a study by Kaner andBond (2004) discovered that employing efficient software testing techniques can greatly decrease the time and expense associated with software development. Nonetheless, many software development projects still don’t use proper testing procedures despite the significance of software testing. A study by NIST (2018) found that insufficient testing procedures are a major factor in software system failures, emphasizing the necessity for software engineering to adopt better software testing procedures.

WHAT WAS DONE? 

Objective: Improve the ability to observe logical analysis in the Writing for Engineering course by enhancing information literacy skills of the students. This will be achieved through collecting and evaluating 30 search results related to the search phrase “Software Engineering” from Google, Google Scholar, and databases using specific criteria and inputting the results into Google Forms for analysis using Excel.

Participants: Students enrolled in the Writing for Engineering course.

Materials: 

  • Search phrase: “Software Engineering” 
  • Search Engines: Google, Google Scholar 
  • Database: ASCE Library 
  • Data Gathering Tools: Google Forms, Excel

Assessments & Measures: 

  • The number of relevant search results collected 
  • The accuracy of the evaluation of search results based on the five criteria (relevancy, authority, accessibility, currency, and expectancy) 
  • The quality of the analysis generated from the gathered information 
  • The quality of the lab reports produced by the students 
  • Pre-Test: To assess the students’ information literacy skills and their ability to observe logical analysis before starting the lab. 
  • Post-Test: To measure the improvement in students’ information literacy skills and their ability to observe logical analysis after completing the lab. 
  • Lab Reports: The quality of lab reports generated by students will be evaluated to measure their ability to apply the skills learned during the lab.

A lab report will be generated to document the process, methods, and results of the lab. The report will include an introduction, methodology, results, and conclusion. The report will detail the number of relevant search results collected, the accuracy of the evaluation of search results based on the five criteria, and the quality of the analysis generated from the gathered information. The report will also include an assessment of the quality of the lab reports produced by the students. 

Process: 

  1. Collecting 30 search results: Ten from each of the three search engines (Google, Google Scholar, and databases) related to the search phrase “Software Engineering”. 
  2. Each search result was evaluated for the following criterias using Google Forms: 
  • Relevancy: Does the search result relate to the search phrase and the research question? 
  • Authority: Is the author credible, and does the information come from a reputable source? 
  • Accessibility: Can the information be accessed easily, and is it available in full text? 
  • Currency: Is the information up-to-date and relevant to the research question? 
  • Bias: Is there any bias or potential conflict of interest in the information presented? 
  1. Inputting search results into Google Forms: The search results will be inputted into Google Forms for analytical purposes. 
  2. Analysis of search results: Gathered information will be analyzed using Excel to observe logical analysis and generate excellent lab reports. 
  3. Calculating the mean for each criterion and generating a graph with excel to figure out the overall quality of the search results. 

Expected Outcome: 

The technical plan aims to enhance students’ research, critical thinking, and information literacy skills to conduct effective and efficient searches, evaluate the quality of information and generate excellent lab reports. By the completion of the lab, the students will be able to observe logical analysis effectively and generate lab reports with high quality and standard.

Google

Google Scholar

Database

DISCUSSION: WHAT DOES ALL THESE MEAN? 

Google presented a diverse set of results, including both academic and non-academic sources. However, its ranking algorithm may not have been able to effectively find and prioritize academic sources relevant to software engineering lab reports. However, Google Scholar presented a more targeted set of results that could better find academic sources relevant to software engineering. The database search tool presented the most targeted set of results but lacked the diversity and comprehensiveness of the general search engines. Overall, each search tool has its own strengths and limitations, and selecting the right search tool depends on the specific needs and requirements of the user. 

In Google search results, the software engineering lab report by ConnectCare was ranked highly in terms of relevance and authority. The report, “effectively demonstrated the design and implementation of the ConnectCare healthcare solution”, can serve as a valuable reference. On the other hand, the “Reporting Experiments in Software Engineering” scored poorly in terms of currency, showing that it may not be the most reliable source for up-to-date information The paper “Enhancing Project-Based Learning in Software Engineering Lab Teaching Through an E-Portfolio Approach” stood out as highly relevant, authoritative, and current, providing a valuable insight into the use of e-portfolios in software engineering education. Conversely, the paper “A survey of controlled experiments in software engineering” scored poorly in terms of accessibility, indicating that it may not be easily accessible to all users. In the database search tool, all lab reports have a higher accessibility rate which makes all reports easier to access. 

In terms of limitations, each search tool has its own algorithm for ranking results, which can affect the relevance and comprehensiveness of the search results. Additionally, user input and search terms can also influence the results obtained. To improve the search process, I can refine their search terms and apply relevant filters to obtain more targeted and relevant results. It is also important to critically evaluate the sources obtained and verify their credibility and relevance to the specific software engineering lab report. Based on the results obtained, it may be beneficial to use a combination of search tools to obtain a more diverse and comprehensive set of results. For example, Google Scholar can be used to obtain academic sources, while general search engines such as Google can be used to obtain a wider range of sources. Filters can be useful in refining search results based on criteria such as relevance, time, and source. I guess I can also maybe consider adding a specific region and year of software engineering to get more targeted up to date results. 

Each search tool has its own strengths and limitations, and selecting the search tool depends on the specific needs and requirements of that I need. To improve search strategies for engineering information, it may be beneficial to use a combination of search tools and to critically evaluate the sources obtained to ensure their relevance and credibility. Future research can focus on developing more targeted and efficient search algorithms that can better show and prioritize sources relevant to software engineering. Effective searching for software engineering lab reports requires careful consideration of the available search tools and their respective strengths and limitations. As Proven in this analysis, Google, Google Scholar, and database search tools can each provide valuable results, but their rankings and algorithms differ, affecting the relevance and comprehensiveness of the results. In conclusion combining different search tools can provide a more diverse and comprehensive set of results. Overall, the process of searching for word phrases can be challenging, but with the right approach and tools, I can get more relevant information. 

CONCLUSION

Our investigation of the effectiveness of search engines and databases in improving information literacy in software engineering showed that both search engines and databases can be valuable tools for conducting research in this field. However, the results also revealed that there are significant differences in the quality and reliability of information available from various sources. It is crucial for researchers to carefully evaluate the information they find to ensure that it is relevant, authoritative, accessible, current, and meets their expectations. This lab activity provided an excellent opportunity for us to develop and apply our research and critical thinking skills and enhance our information literacy in software engineering. Through data collection, analysis, and evaluation, we gained a deeper understanding of the strengths and limitations of different search tools and improved our ability to identify high-quality sources of information. 

REFERENCES 

APA format

GOOGLE: 

GOOGLE SCHOLAR: 

  • Basili, V. R., Profile, V., Phillips, T.-Y., & Metrics, O. M. V. A. (n.d.). Evaluating and comparing software metrics in the Software Engineering Laboratory. ACM SIGMETRICS Performance Evaluation Review. Retrieved April 12, 2023, from https://dl.acm.org/doi/abs/10.1145/1010627.807913 
  • Deep Learning Enabled Semantic Communication Systems | IEEE journals … (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/9398576 
  • Enhancing project-based learning in software engineering … – IEEE xplore. (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/6182725 
  • Evidence-based software engineering for practitioners | IEEE journals … (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/1377125 
  • McGarry, F., Pajerski, R., Page, G., Waligora, S., Basili, V., & Carnegie-Mellon Univ Pittsburgh Pa Software Engineering Inst. (n.d.). Software process improvement in the NASA software engineering laboratory. DTIC. Retrieved April 12, 2023, from https://apps.dtic.mil/sti/citations/ADA289912 
  • Preliminary guidelines for empirical research in software … – IEEE xplore. (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/1027796 
  • Randell, B. (1979, January 1). Software engineering in 1968. Computing Laboratory Technical Report Series. Retrieved April 12, 2023, from https://eprints.ncl.ac.uk/160104 
  • Speech emotion recognition using Deep Learning techniques … – IEEE xplore. (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/8805181 
  • Toward causal representation learning | IEEE Journals & Magazine | IEEE … (n.d.). Retrieved April 12, 2023, from https://ieeexplore.ieee.org/abstract/document/9363924/ 
  • Google scholar. (n.d.). Retrieved April 12, 2023, from https://scholar.google.com/ 

DATABASE SEARCH: 

  • Advanced Software Design and Standards for Traffic Signal Control . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%290733-947X%281992%29118%3A3%28430%29 
  • ASCE Library | Civil Engineering and its practical applications. (n.d.). Retrieved April 12, 2023, from https://ascelibrary.org/ 
  • Economic Analysis of Energy Projects with Uncertainty . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%290733-9402%281990%29116%3A1%281%29 
  • Hydropower Planning in Developing Countries . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%290733-9402%281988%29114%3A1%281%29 
  • Numerical Simulation of a Lab-Scale Molten-Salt External Solar Receiver and Its Experimental Validation. Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%29EY.1943-7897.0000724 
  • Software Engineering for Finite Element Analysis . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/JSDEAG.0004970 
  • Technical Papers Cloud-Based BIM Governance Platform Requirements and Specifications: Software Engineering Approach Using BPMN and UML. Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%29CP.1943-5487.0000539 
  • TECHNICAL PAPERS Distributed Generation with Heat Recovery and Storage . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/full/10.1061/%28ASCE%290733-9402%282007%29133%3A3%28181%29 
  • TECHNICAL PAPERS New Expert Systems in Environmental Engineering . Shibboleth authentication request. (n.d.). Retrieved April 12, 2023, from https://ascelibrary-org.ccny-proxy1.libr.ccny.cuny.edu/doi/abs/10.1061/%28ASCE%290887-3801%281987%291%3A4%28298%29 

APPENDIX 

GOOGLE SCHOLAR: 

GOOGLE SCHOLAR: 

DATABASE SEARCH: 

TECHNICAL PAPERS Distributed Generation with Heat Recovery and Storage