Tag: Ben Williamson

Liked Scientists Seek Genetic Data to Personalize Education by Ben Williamson | @BenPatrickWill (DML Central)

Researchers have begun to propose using genetic data from students to personalize education. Bringing genetics into education is highly controversial. It raises significant concerns about biological discrimination and rekindles long debates about eugenics and the genetic inheritance of intelligence.

Bookmarked How (and Why) Ed-Tech Companies Are Tracking Students’ Feelings by Benjamin Herold (Education Week)

Ready or not, technologies such as online surveys, big data, and wearable devices are already being used to measure, monitor, and modify students’ emotions and mindsets.

Benjamin Herold takes a dive into the rise of edtech to measure the ‘whole’ student, with a particular focus on wellbeing.

For years, there’s been a movement to personalize student learning based on each child’s academic strengths, weaknesses, and preferences. Now, some experts believe such efforts shouldn’t be limited to determining how well individual kids spell or subtract. To be effective, the thinking goes, schools also need to know when students are distracted, whether they’re willing to embrace new challenges, and if they can control their impulses and empathize with the emotions of those around them.

Something that Martin E. P. Seligman has discussed about in regards to Facebook. Having recently been a part of demonstration of SEQTA, I understand Ben Williamson’s point that this “could have real consequences.” The concern is that all consequences are good. Will Richardson shares his concern that we have forgotten about learning and the actual lives of the students. Providing his own take on the matter, Bernard Bull has started a seven-part series looking at the impact of AI on education, while Neil Selwyn asks the question, “who does the automated system tell the teacher to help first – the struggling girl who rarely attends school and is predicted to fail, or a high-flying ‘top of the class’ boy?” Selwyn also explains why teachers will never be replaced.

Bookmarked Comments on ClassDojo controversy (code acts in education)

The educational app ClassDojo has been the target of articles in several British newspapers. The Times reported on data privacy risks raised by the offshoring of UK student data to the US company–a story The Daily Mail re-reported. The Guardian then focused on ClassDojo promoting competition in classrooms. All three pieces have generated a stream of public comments. At the current time, there are 56 comments on the Mail piece, 78 at The Times, and 162 on The Guardian. I’ve been researching and writing about ClassDojo for a couple of years, on and off, and was asked some questions by The Times and The Guardian. So the content of the articles and the comments and tweets about them raise issues and questions worth their own commentary–a response to key points of controversy that also speak to wider issues  with the current expansion of educational technology across public education, policy and practice. ClassDojo has also now released its own response and reaffirmation of its privacy policy.

Ben Williamson addresses a number of questions leveled at Class Dojo, especially in light of the current concern around data. One of the points that he makes that really stuck out was the notion of ‘sensitive data’. Often this is defined by privacy, however as Williamson explains the collection of data over time actually has the potential to turn the seemingly arbitrary into sensitive data.

ClassDojo has been dealing with privacy concerns since its inception, and it has well-rehearsed responses. Its reply to The Times was: ‘No part of our mission requires the collection of sensitive information, so we don’t collect any. 
 We don’t ask for or receive any other information [such as] gender, no email, no phone number, no home address.’ But this possibly misses the point. The ‘sensitive information’ contained in ClassDojo is the behavioural record built up from teachers tapping reward points into the app.

Williamson does however close with a warning, that with GDPR coming in, ‘data danger’ is quickly becoming its own genre:

The risks of ‘data-danger’ for children reported in the articles about ClassDojo doubtless need to be viewed through the wider lens of media interest in social media data misuses following the Facebook/Cambridge Analytica scandal. This presents opportunities and challenges. It’s an opportunity to raise awareness and perhaps prompt efforts to tighten up student privacy and data protection, where necessary, as GDPR comes into force. ClassDojo’s response to the controversy raised by the press confirmed it was working on GDPR compliance and would update its privacy policy accordingly. Certainly 2018 is shaping up as a year of public awareness about uses and misuses of personal data. It’s a challenge too, though, as media coverage tends to stir up overblown fears that risk obscuring the reality, and that may then easily be dismissed as paranoid conspiracy theorizing. It’s important to approach ed-tech apps like ClassDojo–and all the rest–cautiously and critically, but to be careful not to get swept up in media-enhanced public outrage.

Bookmarked Personalized precision education and intimate data analytics (code acts in education)

Precision education represents a shift from the collection of assessment-type data about educational outcomes, to the generation of data about the intimate interior details of students’ genetic make-up, their psychological characteristics, and their neural functioning.

Ben Williamson breaks down the idea of precision through the use of data and how it might apply to education.
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I love Zuckerberg’s positivity. Maybe with a bit more grit and determination he might find a few more million. Really must read The Circle again.
Bookmarked 10 definitions of datafication (in education) by Ben Williamson (code acts in education)

In simple terms, datafication can be said to refer to ways of seeing, understanding and engaging with the world through digital data. This definition draws attention to how data makes things visible, knowable, and explainable, and thus amenable to some form of action or intervention. However, to be a bit more specific, there are at least ten ways of defining datafication.

Ben Williamson documents ten ways of defining ‘datafication’:

  • Historically
  • Technically
  • Epistemologically
  • Ontologically
  • Socially
  • Politically
  • Culturally
  • Imaginatively
  • Dystopically
  • Legally & ethically

This is a good introduction to his book Big Data in Education.

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I have been thinking a bit about technology lately and how we define it. This short reflection is inspired in part by Audrey Watters, Marten Koomen and Ben Williamson. In the end, technology comes in many shapes and sizes.

Bookmarked Globalizing education standards with ISO 21001 by Ben Williamson (code acts in education)

Standards may seem invisible, but they matter—they are consequential to how the world is organized, how people and their behaviour are regulated, and how processes and objects are defined and measured. Those who control standards therefore hold great power to coordinate and organize social, economic, cultural, ethical and political life. Standards constitute societies.

Ben Williamson takes a deep dive into the new ISO 21001 standard designed to structure educational management. This is significant, because such global standards have the potential to define and shape the future. As Williamson explains:

In the tangible world, standards define almost everything. There are standards for the dimensions of kitchen goods and furniture, standard measures, standard fonts and paper sizes, standard economic models, standards for food products, standard business practices, standard forms to fill in, standard formats for cataloguing and indexing, governmental standards, standard classifications of illness and healthiness, standards for ensuring software can operate on computer hardware and that data are interoperable across systems, and much more.

People are standardized too. Standard measures of personality or citizenship, standards of dress and behaviour, standards for credit-scoring and social media profiling, and standards that define social class, socio-economic status, gender, nationality and ethnicity all affect people’s everyday lives. Standard linguistic definitions help us make sense of ourselves and the world we inhabit.

ISO identifies a number of benefits in their press release:

a) better alignment of educational mission, vision, objectives and action plans
b) inclusive and equitable quality education for all
c) promotion of self-learning and lifelong learning opportunities
d) more personalized learning and effective response to special educational needs
e) consistent processes and evaluation tools to demonstrate and increase effectiveness and efficiency
f) increased credibility of the educational organization
g) recognized means to enable organizations to demonstrate commitment to education management practices in the most effective manner
h) a model for improvement
i) harmonization of national standards within an international framework
j) widened participation of interested parties
k) stimulation of excellence and innovation

The problem with this list is that there are so many biases built in and that become a guide for the global operating system.

Bookmarked

Ben Williamson shares a request from his children’s school to provide a t-shirt to make a Growth Mindset cape. He unpacks this and shares his concerns about a focus on moral implications and economics deriving from the work of James Heckman.

Liked PISA for personality testing – the OECD and the psychometric science of social-emotional skills by Ben Williamson (code acts in education)

SSES extends the reach of datafication of education beyond school walls into the surveillance of home contexts and family life, treating them as a ‘home learning environment’ to be assessed on how it enables or impedes students’ development of valuable socio-emotional skills

Ben Williamson provides a (very partial) overview of some of the key features of SSES. However, it does raise a few headline points:

SSES extends international-large scale assessment beyond cognitive skills to the measurement of personality and social-emotional skills

SSES will deliver a direct assessment instrument modelled on psychological personality tests

SSES enacts a psychological five-factor model of personality traits for the assessment of students, adopting a psychometric realist assumption that personality test data capture the whole range of cross-cultural human behaviour and emotions in discrete quantifiable categories

SSES extends the reach of datafication of education beyond school walls into the surveillance of home contexts and family life, treating them as a ‘home learning environment’ to be assessed on how it enables or impedes students’ development of valuable socio-emotional skills

SSES normalizes computer-based assessment in schools, with students required to produce direct survey data while also being measured through indirect assessments provided by teachers, parents and leaders

SSES produces increasingly fine-grained, detailed data on students’ behaviours and activities at school and at home that can be used for targeted intervention based on analyses performed at a distance by an international contractor

SSES involves linking data across different datasets, with direct assessment data, indirect assessments, school admninistrative data, and process metadata generated during assessment as multiple sources for both large-scale macro-analysis and fine-grained micro-analytics–with potential for linking data from other OECD assessments such as PISA

SSES uses digital signals such as response times and keystrokes, captured as process metadata in software log files, as sources for stealth assessment based on assumptions about their correlation with specific social-emotional skills

SSES promotes a therapeutic role for education systems and schools, by identifying ‘success’ factors in SELS provision and encouraging policymakers to develop targeted intervention where such success factors are not evident

SSES treats students’ personalities as malleable, and social-emotional skills as learnable, seeking to produce policy-relevant psychometric knowledge for policymakers to design interventions to target student personalities

SSES exemplifies how policy-relevant knowledge is produced by networks of influential international organizations, connected discursively and organizationally to think tanks, government departments and outsourced contractors

SSES represents a psycho-economic hybridization of psychological and psychometric concepts and personality measurement practices with economic logics relating to the management of labour market behaviours and human resources