MBIS4009 Professional Practice in Information Systems Essay Sample

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MBIS4009 Professional Practice in Information Systems Essay Sample

Assessment Description

Students are required to analyse the below situations and evaluate the consequence of the actions taken. Additionally, taking a stand, students should establish an argued conversation with ChatGPT/Bard about the topic.

Your essay should be a synthesis of ideas researched from a variety of sources and expressed in your own words. It should be written in clear English and be submitted at the end of Session 5 in electronic format as either a Word document or a pdf file. AI is not allowed to be used in this assessment. This electronic file will be checked using Turnitin for any evidence of plagiarism, including the use of Artificial Intelligence (AI). You are expected to use references in the normal APA referencing style.

CASE TO ANALYSE

The Ethical Dilemma of Assessing Students with AI

Using Artificial Intelligence (AI) for assessing and marking students could be a very popular practice in the future. In the current state of AI, it involves several ethical issues, such as fairness, personalization, data privacy, transparency, among others. Drawing on relevant ethical theories, analyse the consequences of the implementation of such practice in Australian Universities.

Your report should explore this dilemma by presenting arguments grounded in ethical theories and supported by research sources. Consider the following points:
Introduction: overview, importance.

Ethical Theories: discuss applied to this case at least two ethical theories seen in class, implications of each theory, and main dilemmas; provide examples.

State your position and Recommendations: state your position and provide a rationale.

Conclusion: summarize the key ethical considerations

References: utilize at least six credible research sources to support your arguments.

Detailed Submission Requirements

Before submission, students ensure the submitted work satisfies the following requirements:

• The assignment is to be written in a report format. It must have separate sections.

• The essay should additionally, include an Introduction, Conclusion and References

• Submit as a PDF or Word document through the Turnitin assignment submission tool on Moodle.

• Include a title page that has your name, subject, date, report title and WORD COUNT. Please do not include an assignment cover page as this will match with other students at AIH.

• The assignment should not exceed 1,100 words with a minimum of 1,000 words, excluding references.

• Your conversation with ChatGPT/Bard should be added as an Appendix

Solution

Introduction

The AI (Artificial Intelligence) will play a vital role in future period for assessing and marking students. There are a number of benefits of using AI for education sector. One of the major benefits is its capability to personalize the learning experience for every student. In spite of its significance, currently, there are a number of ethical issues involved in it like transparency, fairness, confidentiality, and many more. In this aspect, present report contains the evaluation of the application of AI practices in Australian Universities by applying ethical theories.

Further, recommendations are also provided for addressing those issues for university assignment help

Ethical theories

With the analysis of ethical theories, moral issues contained in AI for students can be evaluated effectively.

Utilitarianism (Consequence based):

This theory is result-oriented where the action is ethically correct if its results satisfy people or make people happy. If the results are not satisfied or do not make people happy the actions are not considered right. Considering the current situation from the context of Utilitarianism states that if the result of applying AI to assess students’ leads to satisfied students and universities or happy students, then the context can state to be morally correct (Lim et al. 2023).

In the present situation, if AI is applied to assess students, some students may get high marks for similar works based on keywords included or algorithms used and this could lead to fairness issues. To assess students, their co-curricular activities need to be assessed well this affects how each student is assessed and has a different base for assessment. Overall students are not satisfied with differentiated results, and thus this action is morally incorrect. Many authors criticise this theory which states that a moral action that does not lead to happy results cannot be considered an immoral action. Since during making decisions decision is good for one and unfavourable for another and thus based on morality and happy results it cannot be considered moral (González-Calatayud et al. 2021).

For example, 2 students have performed well, and their way of writing exams are different i.e. one makes use of examples while the other makes use of charts and tables for easy understanding. Based on the use of words their assessment is different, and thus there are high chances that one of them gets more marks as compared to others and this is a sort of biased assessment since both examples and use of graphs are relevant ways of answering questions. This biased assessment leads to unhappy students and thus using AI in student assessment is unethical as per Utilitarianism theory.

Deontology (Duty-based):

This theory states that there is always need to follow rules and principles regardless of what results it leads to. Deontology theory reflects that following roles and duties is equally important even if it leads to wrong or negative outcomes. The current scenario of using AI to assess and give marks to students is ethically incorrect as the theory states that the actions ensure fairness among students which AI does not ensure with its biased assessment (Kumar, 2023). There is no accuracy and reliability of the markings and assessment based on the notes, type, of content and approaches used AI assessment method differs as it uses a single rubric method, though the student's answer may be right based on other approaches based on their understanding, and thus AI based students assessment is considered to be unethical (Smuha, 2020).

For ethical use of technology principle, AI could easily be hacked and use student information from different perspectives for student assessment and thus it leads to issues of data privacy and thus it is unethical. As per deontology theory, the context of using AI for student assessment is unethical (Holmes and Porayska-Pomsta, 2022).

For example, fairness and equity are one universal principle that need to be followed and every person must be respected and have fairness to consider those acts as ethical. In Australian universities if one student writes exams that include examples as stated in the rubric while another student writes the same answers in tabular and pictorial formats and makes use of images to write the answer based on strict rubric guidelines and algorithms set, later student is more likely to get less marks though the primary aim is to review student's understanding of the topic.

AI does not consider unique patterns of human nature and thus leads to a biased nature that suits close to their assessment approaches, and this leads to biased results and a lack of fair decisions. There are further ethical dilemmas associated with this where following principles sometimes leads to harm to others.
State your position and recommendations

As per the analysis of the above theories and analysis of AI from different sources, it is been identified that the current context to use AI to assess and grade students seems to be unethical (Hendricks et al. 2020). AI seems to use different bases for different students as per the content they have written approach they have used to showcase their knowledge and more. Since humans have different personalities to showcase their knowledge. It is recommended to automate various analytical tasks while reviewing students' assessments and assessing their creativity needs to be done manually (Wang and Lin, 2023). Additionally, transparency and accountability of AI algorithms and decision making procedure should assured by Australian Universities. Student must recognize the manner of working of AI system, comprising the method of data collection, its usage, and analysis.

Conclusion

It has been concluded that the situation to use of AI for the assessment and marking of students in Australian universities is found to be unethical since it will conflict with principles of fairness, equality, accuracy, ethical use of technology and more. Utilitarianism found that the creative nature of showcasing knowledge can be ignored by AI based on its strict algorithms and this will make students unhappy and thus the act is unethical. It is recommended to use AI as the part of assessment for automation and accurate results, and need not be used as a whole for assessing and automating the whole process.

Reference

González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467.

Hendrycks, D., Burns, C., Basart, S., Critch, A., Li, J., Song, D. and Steinhardt, J., 2020. Aligning ai with shared human values. arXiv preprint arXiv:2008.02275.
Holmes, W. and Porayska-Pomsta, K. eds., 2022. The Ethics of Artificial Intelligence in education: Practices, challenges, and debates. Taylor & Francis.

Kumar, R., 2023. Faculty members’ use of artificial intelligence to grade student papers: a case of implications. International Journal for Educational Integrity, 19(1), p.9.

Lim, T., Gottipati, S. and Cheong, M.L., 2023. Ethical Considerations for Artificial Intelligence in Educational Assessments. In Creative AI Tools and Ethical Implications in Teaching and Learning (pp. 32-79). IGI Global.

Smuha, N.A., 2020. Trustworthy artificial intelligence in education: Pitfalls and pathways. Available at SSRN 3742421.
Wang, C.Y. and Lin, J.J., 2023. Utilizing artificial intelligence to support analyzing self-regulated learning: A preliminary mixed-methods evaluation from a human-centered perspective. Computers in Human Behavior, 144, p.107721.

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