Digital Disruption Changes Learning Process, Educators’ Mindset

The Fourth Industrial Revolution, or Industry 4.0, has led to digital disruption (cloud computing, internet of things, artificial intelligence, 3D printing, blockchain, big data, smartphones) and brought radical changes in the economic, social and cultural fields.

Disruption brings uncertainty. As a result, first, an institution's ability to survive and develop depends on its capacity to respond to the challenges of uncertainty.

Second, disruption forces us to readjust our cultural strategies, especially the education system. The answer is innovation, which is the result of collaboration. So in the future, collective intelligence will be very decisive because it frames professional qualifications as the engine of innovation.

Innovation requires special competencies in hard skills (cloud computing, artificial intelligence, analytical-critical reasoning, resource management, user experience design, development engineering) and soft skills (creativity, communication, collaboration, adaptation and time management). Mastering these various skills requires changing the education system so the learning focus is on creative and innovative problem solving.

Also read:

> Responsibility for Education

> Maintaining Teacher Quality

The problem is, the learning model at schools and universities still revolves around ordinary cognitive tasks: listening, reading, memorizing, comprehension and exams. This learning model, from the perspective of Bloom's taxonomy (Anderson & al, 2001:31), has not moved from lower-order thinking. Skills that result from this learning method are increasingly being replaced by cloud technology and automation.

The pattern of the Third Industrial Revolution still focuses on training as many workers as possible in manufacturing and trade. The subjects are standardization, uniformity and mass production through classroom learning (Trilling & Fadel, 2009: 13). In fact, the skills needed in the era of disruption require higher-order thinking and learning, such as analysis, evaluation and being creative thinking in terms of critical analysis.

What kind of knowledge, skills and competencies do young people need to successfully deal with digital disruption?

Analytical thinking is a tool for evaluating various resources, data, facts, phenomena and findings to give meaning and representation. This ability is decisive in developing solutions and decisions from a set of useful information (Wilen, 2018: 144-145). The critical aspect lays in assessing the validity of ideas, offering rational judgments and identifying social irregularities (injustice, discrimination, manipulation) from the information.

All of these skills require change in the education system.

The change will be successful if the educational direction can answer the following three questions.

One, what kind of knowledge, skills and competencies do young people need to successfully deal with digital disruption? Two, how will the learning model help prepare young people to deal with the demands of digital disruption? Three, what can be done to help educators change their mindset to adapt to the demands of the new learning model that focuses on the learner, not the educator?

Skills in the disruptive era

To answer the first question, six types of skills are needed in the disruptive era: (1) conveying ideas and coding literacy; (2) analytical and critical thinking; (3) communication; (4) information technology; (5) network organization and management; (6) innovation planning and organization.

These six skills presuppose specific learning patterns. First, ask detailed questions. Second, evaluate information. Third, seek evidence. Fourth, compare and analyze. Fifth, consider the context so learners can creatively solve problems. Educators must therefore have skills in designing a variety of concrete projects so learners can take context into account while working on them.

Creative learning model

Learning models must sharpen analytical-critical thinking skills to solve problems creatively. The author proposes five training frameworks: (1) abductive reasoning; (2) five steps to scientific problem solving; (3) design thinking; (4) computational thinking; and (5) critical discourse analysis (CDA).

Also read:

> Questioning Neutrality in Education

> Commercialization of Education

First, abductive reasoning is neither deduction nor induction, but a form of thinking that starts with observation that then proceeds to finding the easiest explanation that approaches the truth. The possible answers are many, so it is hypothetical. Abductive reasoning is a logical conclusion that still leaves open the possibility of various solutions: "the most likely" or "the most reasonable".

Indeed, it is precisely this openness to possible solutions that helps the creative learner be unafraid of having different opinions, which is conducive to innovation. Learners are encouraged to dare to experiment, think differently and be creative.

Second, the five steps of solving problems are: (1) uncovering problems that are still undefined; (2) formulating the problem clearly and distinctly; (3) suggesting possible solutions to the problem by testing the proposal to be used as a guiding idea for observation; (4) providing reasons, evaluations, or consequences for verification; and (5) applying, testing and following up on the selected solutions or verifying the hypotheses (Dewey, 1933).

This exercise develops learners skilled in formulating defined problems, proposing creative solutions and familiar with being reflective.

Third, design thinking is the cognitive, strategic and practical process to develop design concepts that designers usually use. This way of thinking is supported by nonverbal means, graphics, or modeling media. It combines logic, intuition and systematic thinking by applying productive reasoning (logical abduction).

The steps are (Pressman, 2019): (1) empathize and gather information; (2) analyze and define the problem; (3) create ideas that have the potential to solve the problem; (4) synthesize through modeling and implementation; (5) evaluate critically.

Also read:

> Notes on 75 Years of National Education

This learning method develops empathy, confidence, communication, flexibility and openness. Empathy leads to a commitment to solving problems. This skill brings together situational awareness and empathy for the birth of new ideas

Fourth, computational thinking is a way of thinking that is oriented to solving problems by designing systems, so they can be represented and run more effectively by information processors (Mailund, 2021).

Its five components are: (1) decomposition, or breaking down complex data, processes or problems into simpler parts; (2) recognizing patterns, or observing data patterns and regularities and then relating them to similar problems; (3) abstraction, to formulate the central problem by reducing information superfluous to solving the problem; (4) algorithms, or designing step-by-step problem solving instructions for similar purposes; (5) evaluation, to ensure that the solution is correct (Mailund, 2021:44-46).

This exercise familiarizes learners with thinking systematically, methodically, coherently and creatively so they are able to optimize the use of big data to improve performance.

Fifth, critical discourse analysis sharpens minds so they are critical, observant and sharp in analyzing rhetoric, manipulation and misdirection in communication. The assumption is that behind language is ideology, so language is used as an instrument of power.

The steps are (Fairclough, 2010:234): (1) focusing on “social irregularities” (injustice, discrimination, conflict, manipulation, negative bias, scapegoating); (2) identifying barriers to addressing the “social irregularities”; (3) does social order “need” social disorder?; (4) propose solutions to overcome the obstacles.

Through this exercise, learners develop to care about social inequalities, discrimination, injustice and intolerance, and are challenged to offer solutions. Learners become critical of rhetoric, manipulative discourse, misleading and indoctrination. Learners are equipped with the tools to counter radical ideas and filter hoaxes.

The five learning methods above answer concerns about how to provide a basic framework for integrating character education into every subject or lesson.

Changing educators’ mindset

Nowadays, it is increasingly acknowledged that the pressure of learning science, technology, engineering, mathematics (STEM) must be balanced with the liberal arts to help develop the mental power and character of learners and all their thinking resources, whether critical, analytical or creative.

Liberal arts today include literature, philosophy, social sciences, ethics and esthetics to help develop open and flexible thinking.

To adapt to the changing demands of the new learning model, educators’ mindset must also change: the focus of learning is no longer the educator, but the learner.

A situation of learning needs to be created so that learners grow passionate about exploring and experimenting.

Thus, educators must adapt to their six new functions as: (1) designer of learning empowerment; (2) information source or informant; (3) manager of problem-solving ecosystem; (4) facilitator; (5) motivational resource for innovation; (6) role model of constant learning and networking (Gleason, 2018; Jukes & Schaaf, 2019).

Kompas

Haryatmoko

The purpose of these six functions is to encourage the learner’s creativity. A situation of learning needs to be created so that learners grow passionate about exploring and experimenting. As such, educators must be good listeners and willing to ask many questions.

Educators are willing to partner with people who know more and are motivated to build space for preparing prototypes for small-scale experiments. Failure is no longer taboo in the learning process, because it can be reframed into valuable lessons.

Haryatmoko, Member, Cultural Commission of the Indonesian Academy of Sciences (AIPI)

This article was translated by Kurniawan Siswoko.