Abstract
With the ever higher costs of human-led instruction, much of adult electronic learning (e-learning) has become automated, independent, dispersed to open-source locales, and open learning. There has been a growing focus on adult learner self-initiative in identifying and pursuing learning opportunities independently. Such discovery learning is not just for practical and informal work but has now reached well into formalized trainings and deeper lifelong learning. This phenomenon has led to a variety of methods for adult learner self-assessment of their own learning—ranging from pre-determined scripted responses to live human feedback to mixed-methods feedback. Feedback loops for learner self-assessment are critical to support learner engagement, actual learning, learner self-efficacy, decision-making, skills acquisition, and human development; these also enhance mutually supportive collaborations and innovations between co-learners; and they enable workplace and higher education credentialing needs. This chapter highlights the importance of self-assessments and learner feedback in e-learning, and proposes some foundational design strategies.
TopIntroduction
“If you know the enemy and know yourself, you can win a hundred battles without a single loss.” – Sun Tzu in The Art of War (6th century BC)
Knowledge of the self may be hard to come by in a range of fields, particularly when the learner is a novice or an amateur. However, the current electronic learning environment encourages exploration and requires enriched self-assessment feedbacks for modern online learners—in order to enhance the online learning experience.
Contemporary adult electronic learning (e-learning) involves both formal and informal e-learning. Formal e-learning for adults involves those sponsored by work places and institutions of higher learning. These may include full-length courses, simulated experiences, project-based learning, problem-based learning, and field trips. These may include formal training that may earn university or college credit for prior experiential learning (assessed by professionals in the field based on the adult learners’ portfolios). Informal e-learning refers to the pursuit of knowledge and skills outside any formal workplace or educational structure. Amateurs, novices, and experts will pursue informal e-learning, which may involve automated experiences, modules, and courses; educational gaming; virtual simulations; 3D immersive spaces; discovery learning spaces and exploratoriums; and virtual communities of practice around shared interests. Some types of informal learning involve casual play, a form of entertainment. Contemporary adult learners may sample widely across both the formal and the informal, with each type of learning supplementing and enhancing the other.
The half life of information is getting ever-shorter, and the freshly-minted degrees date out in terms of their informational value within a few years. To function, much less compete, in the modern world, people need to learn continually. This pressure has clashed with another reality—the need for higher education and corporate cost-savings. This economic reality has meant increasing student-to-faculty ratios in academia. Greater demands on faculty time [“the need to be seen as 'research active', the generation of funding, public service, and intra-institutional administration” (Yorke, 2003, p. 483)] also detracts from instructional pursuits. A tougher economy has also meant a diminishment of human-facilitated trainings and a turning to computer-based trainings.
Recent moves to offer ubiquitous mobile learning for “anytime, anywhere” learning has focused on meeting the needs of busy adult workers. Adult learners want hands-on applied learning in real context; they want to make decisions about their own learning; they tend not to like being assessed (Merriam & Caffarella, 1999). This mix of realities has led to a great importance of adult e-learner self-assessment delivered by Web.
Key Terms in this Chapter
Learned Dependence: The subjective perception of a learner’s reliance on the instructor to define a task, which restricts the learner’s full capabilities.
Formative: Contributing to development (as in an assessment that contributes to the learning rather than assessing attained knowledge or skill levels only).
Individualized: Customized, unique or specific to the individual.
Help-Seeking: The act of looking for assistance or support—from technological systems, socio-technical systems, experts, and others.
Monitoring: Surveillance.
Artificial Intelligence (AI) Tutor: A robot that provides tutor support to a learner based on artificial intelligence designs.
Andragogy: Instructional strategies for teaching adults.
Self Assessment: To evaluate oneself and one’s abilities based on evaluative feedback and other information.
Forage: To seek provisions (of information).
Discovery Learning: Learner-driven pursuit of knowledge and skills, often through designed online learning spaces.
Problem Solving Virtual Communities (PSVCs): Virtual communities built around shared problem-solving and related learning, troubleshooting, and creativity.
Artificial Intelligence (AI): The emulation of human intelligence (in terms of assessment and decision-making) by machine intelligence or a software program.
Autonomous: Independent, self-governing, self-deciding.
Branching Logic: A type of customization that changes the course of learning based on learner performance.