Digital Badges and Ethics: The Uses of Individual Learning Data in Social Contexts James E. Willis, III Joshua Quick Daniel T. Hickey Indiana University Indiana University Indiana University 1900 East Tenth Street, Room 504 1900 East Tenth Street, Room 503 1900 East Tenth Street, Room 506 Bloomington, Indiana 47406 Bloomington, Indiana 47406 Bloomington, Indiana 47406 001-812-856-1483 001-251-463-6070 001-812-856-2344 jaedwill@indiana.edu jdquick@indiana.edu dthickey@indiana.edu ABSTRACT 1. INTRODUCTION Empirical evidence contained in open digital badges has the Amongst recent developments in educational technology capability to change educational curricula, assessments, and innovation, open digital badges are positioned to have ever- priorities. Because badge data in educational, social media, increasing influence on learners, teachers, institutions, and and workforce contexts is publicly available, questions of the workforce [1]. This influence changes several major privacy and ethics should be scrutinized. Due to change components of education: transparency of assessments, driven by digital transparency, ethical questions at the validated evidence of learning, granularity in skills intersection of learning analytics and the data contained in development, and demonstration of skills in digital social badges poses three distinct, yet related questions: within networks [2]. Perhaps the final point, the publicity of such learning analytics systems, can the use of educational data learning, is the least explored component of badges in digital badges be used in a predictive manner to create a research to date. Simply, what can be known about the deterministic future for individual learners? Can badge data effect of badges networked via social media on various that is freely and openly accessible in social media be used outcomes like employment is tenuous at best [3]. The social against individuals if it exposes intellectual weaknesses? aspect of digital badges includes a host of questions And, can the student data in badges be isolated to exploit pertaining to what data is available and to whom, how it is particular skills for nefarious reasons, i.e. surveillance or distributed and acquired by other parties, and what occurs hacking? These questions address ethical principles of with individual and aggregate learners’ data. In an age of human autonomy, freedom, and determinism. web crawlers, data collection firms, and predictive algorithms, these questions warrant exploring. Categories and Subject Descriptors The possible educational data contained in badges, K.4.1 [Public Policy Issues]: Ethics. including assessments, validation, and demonstration of skills, is of value as one aspect of a wider and growing General Terms body of research in learning analytics [4]. The open digital Algorithms, Design, Experimentation, Security, Human badge as an artifact of learning contains a key social aspect Factors, Theory, Legal Aspects that conventional transcripts did not [5]. While learners may elect to distribute digital badges across social media Keywords outlets (like Facebook, LinkedIn, or Twitter), traditional Ethics, Open Digital Badges, Education, Learning collegiate transcripts are typically withheld and only Analytics, Social Media, Networks, Autonomy, Human distributed to another party at the learner’s explicit request. Freedom, Determinism. This availability of student data, though freely and willfully disseminated in a learner’s digital network, poses specific ethical concerns. The morality of data usage is certainly heterogeneous in today’s widely-expanding ecosystem of educational technology, but the specific ethical issues with Copyright © by the paper’s authors. Copying permitted for digital badges concern the broad implication of human private and academic purposes. autonomy, freedom, and determinism. The research In: D. Hickey, J. Jovanovic, S. Lonn, J.E. Willis, III (eds.): questions pertaining to badges, then, are meant to pivot Proceedings of the Open Badges in Education (OBIE 2015) Workshop, Poughkeepsie, New York, USA, 16-Mar-2015, from three distinct, yet interrelated, modalities of the published at http://ceur-ws.org. intersection of digital ethics and learning analytics: • Within learning analytics systems, can the use of badge ecosystems could strengthen a learning analytics’ educational data in digital badges be used in a predictive strength. For example, with the completion of predictive manner to create a deterministic future for several badges in both curricular and extra-curricular individual learners? activities, data points could be amalgamated to further • Can badge data that is freely and openly accessible in bolster a student’s educational strengths and support social media be used against individuals if it exposes possible weaknesses. The specificity of assessment data, intellectual weaknesses? where final grades in college courses could be aligned with • Can the student data in badges be isolated to exploit performance data in badges, could provide extremely particular skills for nefarious reasons, i.e. surveillance valuable information not only to the learner, but also the or hacking? institution supporting the learner, as well as the businesses developing learning analytics systems. 2. ETHICS, EDUCATIONAL As analytics systems increase their capability of predicting TECHNOLOGY, AND BADGES student outcomes, it may be difficult to distinguish between With the expansion of educational technology, some work the strength of the predictive algorithm and the role of is being done at the intersection of ethical theory and determinism as it affects students. This is not to say that the learning analytics [6]. Some propose ethical frameworks same would be true of digital badges, though. In this for development [7], while others appeal specifically to instance, determinism would entail the ability to either known problems in the legal use of student data in analytics sequentially offer badges to purposely build a set of skills systems [8]. This is a growing domain of research in the in a learner without his/her explicit knowledge or to broader implications of how educational technology affects suggest that a self-fulfilling prophecy of ability would be student growth and development. set forth with badge data. A student’s interaction with content leading to a badge may be examined for Though some commentators have noted the potentially- motivational aspects, perhaps even for so-called harmful aspects of having open data in social networks, to gamification reasons. However, could the data contained date there has been scant studies of ethical issues in open with badges be used to constrain a determined future? digital badges [9]. As research in the ethics of educational Meaning, if students are directly motivated to achieve technology expands, a myriad of potential problems looms certain badges, their interests may be piqued either with the [10]. To bridge this gap, targeted ethical questions must be content or with simply obtaining a badge; the question, specific enough to demonstrate applicability, but also be then, is what effect the badge may have on future generalizable enough to warrant attention outside of the educational choices. Today’s use of digital badges is often broadly-considered technology. to enhance learning and provide open and transparent Due to their connection with social networks, availability evidence of learning. It is impossible to say if this will of meta-data, and transparency of learning, digital badges continue, and what possible effect badges may have on face important ethical questions best formulated within the learners’ educational choices. A determined future, one larger context of learning analytics. shaped by an algorithm targeting content and ability, may not be suitable to human freedom and autonomy. 3. PREDICTION AND BADGE DATA: A Important to learning is the chance – and the eventuality – DETERMINISTIC FUTURE? of failure. Learning and carrying on from failure is a Learning analytics systems are becoming increasingly hallmark of resilient students who become as self- powerful tools to help students utilize educational data to actualized as possible. Badges can certainly help mitigate achieve academic success [11]. Such data points are ever- educational failure because they are used to supplement precise, refined by multiple cohorts, experiments, and through micro-credentialing, build on skills to be successful digital developments. One of the drivers of such in other educational contexts, and provide a lasting record development is statistical regression which helps predict of one’s accomplishments. Yet, human freedom and when students need help [12], what classes might be autonomy must be examined in light of these technological beneficial in customized sequences [13], and how certain developments. If learning analytics in the systemic sense interventions benefit different types of students [14]. The and digital badges in the individual sense are able to robustness of learning analytics systems are built with data absolutely minimize failure, could learners suffer from not refined over time and with evidence of successful student having to form resilience? The possibility of minimizing outcomes [15]. failure and preventing failure is determinism for individuals, though the data available in digital badges Open digital badges contain multiple points of valuable poses numerous ethical questions related to public educational data including assessments, specific skills disclosure of student data. Learning analytics systems used development, and validation amongst others. Built within at schools are controlled by regulations (like FERPA), and learning analytics systems, the evidence presented in are thus “closed” systems, whereas open badges make badges can help detail a student’s educational strengths and educational and learning data public. weaknesses. Further, the data available in well-designed 4. PUBLIC LEARNING DATA AND publishing particular data points. Further, if such NEGATIVE CONSEQUENCES algorithms can threaten learning weaknesses in individual One of the benefits of open digital badges is that they can learners, the same may be true for the entire badge publically demonstrate a set of skills; downloadable into ecosystems because a badge’s validity, no matter the various social media, badges can evidence real learning expertise involved in the content development, deployment, [16]. If a learner chooses not to disclose a badge on social and verification, could be threatened. The possibilities media, but instead download the badge into an email highlighted within learning analytics systems and in format, the data can still be used in a closed system with individual learning may well point to more sinister uses of employers as a link on a resume [17]. The social aspect, data. then, stems from the ability of the learner to disclose proof of learning that, heretofore, was protected or closed 5. LEARNING DATA USED FOR information. The evidence, the proof of learning, may NEFARIOUS PURPOSES transform education through transparency [18]. Similarly, The increasing specificity of learning data within digital badges may well transform workforce skills demonstration badges may lead to nefarious uses of that data in aggregate through the use of social media sites like LinkedIn [19]. or individual cases. The use of predictive models in learning analytics coupled with evidence of skills The data contained in digital badges, depending on the development in digital badges disseminated across social issuer and what the learner chooses to display, can be quite media could help companies, governments, and perhaps detailed and specific. Combined data of multiple badges even disreputable organizations recruit for nefarious could be used by web crawlers or data companies to build purposes like hacking or surveillance. Furthermore, if individual profiles of learners, including what content they learners are completing badges “recommended” to them for would like to purchase, what specific skills could be the ulterior motives of developing certain skills, could such utilized in the workforce, or how future content might be information be used against them if they later refuse to developed to attract similar learners. To illustrate the point, participate in questionable activities? This may sound the evolution of massive open online courses (MOOCs) rather extreme, but when educational data is used across struggled to catalyze around a business model, though social media and within predictive systems, it is impossible recently what has emerged are verified certificates that can to state how such data might be used. Additionally, while be quite lucrative to students and recruiting companies this may not come to fruition, the logical extremity is alike [20]. While it is yet not possible to say if MOOCs can useful to examine the possible uses of future data. be digital headhunters, the same may be true of digital badges in the near future. If companies seek highly specific Ethically, the question of learners knowingly or skills that can be learned through competencies (like unknowingly participating in skills development for software programming, for example), perhaps badge data nefarious purposes is a question of human freedom, and would provide not only individual identifiers but also ultimately it rests with the actions of the learner. However, scoring and assessment data to substantiate such skills. the possibility of future manipulation certainly conflicts with how popular notions of badges today include that of Beyond marketing, though, the question must be posed as supplementing learning, offering opportunity for job to whether such data could be used to locate and isolate creation and advancement, and branching learning into individual learning weaknesses. Assessment data social spheres. availability in social media means that a learning profile could be assembled to indicate what constructs a learner 6. CONCLUSION does not understand or habitually misses. Such data may Open digital badges are changing the educational prove dubious if used against the learner in future opportunities for learners of today and tomorrow. The assessments purposely generated to exploit such intersection of learning analytics systems that may weaknesses, targeted marketing, or perhaps even incorporate badges, as well as the possibility of learners to exploitation if threatening job security. The ethical question disseminate evidence of learning across social media of such data usage becomes more complex, too, when platforms, creates unique ethical questions that fit within considering what safeguards could be enacted; overreach the larger discussion of machine learning. The uses of data and paternalism may also hinder a learner’s autonomy, for prediction, isolation of strengths and weaknesses, and freedom, and right to fail at a task. potential manipulation have direct consequences for Questions about what data points are useful in social media questions of human autonomy, freedom, and determinism. contexts are open for debate, but generally arguments seem Such scenarios described herein may appear to be to tentatively hinge in favoring the position of the exceedingly negative or dystopic to some readers. While individual learner’s choice to expose or withhold true that some of the scenarios may or may not come to information. This matter becomes an issue of privacy fruition, they function here not only as a thought within digital badge ecosystems, however, when students experiment, but also as a model of what may go awry as may or may not fully comprehend the possible outcomes of increasing amounts of personalized data are distributed, shared, and examined online. It is also a model for how Higher Learning. 46, 1, 21-25. data crawlers may use student data with present DOI=10.1080/00091383.2014.867206. technologies. While not a warning in the formal sense, such [6] Slade, S. and Prinsloo, P. 2013. Learning analytics: thought experiments are useful to describe how the ethics Ethical issues and dilemma. American Behavioral of technology, broadly understood, ought to enter into Scientist. 57, 10. 1509-1528. development discussions. DOI=10.1177/0002764213479366. Like other ethical discussions concerning digital learning [7] Willis, III, J.E. 2014. 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