For the past several years the popularity of learning in the online learning environment has been steadily increasing, however, when the Covid-19 pandemic hit and the world went into various versions of lockdown, the need to ensure that education could continue was paramount. A lot of institutions had some fragmentary ideas of how distance learning would operate and many of them looked to the online space. However, online learning without the appropriate frameworks being implemented would still need to be linked to the traditional learning approach resulting in the introduction of blended learning for many educational institutions. Due to the need to ensure learning continued throughout lockdown, most institutions’ implementation provided the opportunity for many learning curbs that institutions needed to grow through, however, the issue of how much sharing and rephrasing as well as online assistance through artificial intelligence (AI) systems were blurring the rules. One of the concerns have been, is it bending of the rules and ethical stance or completely changing it. Similar to a traditional learning environment, if someone else wrote your assignment it would be considered cheating–why would this be different if the AI system was the “someone else”? The learner justification has been, for a long time, that if there is no rule forbidding it–there is not rule, per say, to break. This paper explores if there is a rule and how does it work and if there is no rule, should there be one and how should it be integrated. Often, the assumption that educational institutions employed were that learners signing integrity statements and the like would be sufficient to hold the learner to an ethical standard, however, this has failed in many instances due to the “if there is no rule, it cannot be broken” stance. This paper addresses the ethical issues one would face in an online learning environment, with special attention to fair use of copyright protected materials and the impact of relying on AI to pass off protected copyright works as one’s own.

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Understanding the Ethical Conundrum of Digital Learning

  • Natalie Martin

摘要

For the past several years the popularity of learning in the online learning environment has been steadily increasing, however, when the Covid-19 pandemic hit and the world went into various versions of lockdown, the need to ensure that education could continue was paramount. A lot of institutions had some fragmentary ideas of how distance learning would operate and many of them looked to the online space. However, online learning without the appropriate frameworks being implemented would still need to be linked to the traditional learning approach resulting in the introduction of blended learning for many educational institutions. Due to the need to ensure learning continued throughout lockdown, most institutions’ implementation provided the opportunity for many learning curbs that institutions needed to grow through, however, the issue of how much sharing and rephrasing as well as online assistance through artificial intelligence (AI) systems were blurring the rules. One of the concerns have been, is it bending of the rules and ethical stance or completely changing it. Similar to a traditional learning environment, if someone else wrote your assignment it would be considered cheating–why would this be different if the AI system was the “someone else”? The learner justification has been, for a long time, that if there is no rule forbidding it–there is not rule, per say, to break. This paper explores if there is a rule and how does it work and if there is no rule, should there be one and how should it be integrated. Often, the assumption that educational institutions employed were that learners signing integrity statements and the like would be sufficient to hold the learner to an ethical standard, however, this has failed in many instances due to the “if there is no rule, it cannot be broken” stance. This paper addresses the ethical issues one would face in an online learning environment, with special attention to fair use of copyright protected materials and the impact of relying on AI to pass off protected copyright works as one’s own.