Training and Development in Organizations: Now More Than Ever
As training and development come to the forefront of the national debate, the pace of research activities by basic and applied psychologists from various areas has also quickened. Fortunately, training researchers from different areas such as industrial/organizational, cognitive, and human factors psychology, as well as instructional design and computer science, are beginning to share research ideas and findings. This interdisciplinary approach is perhaps best exemplified by the founding of a new journal, the Training Research Journal, which is aimed at researchers from various disciplines involved in training and development.
In the following paragraphs, I present three areas of research that are currently attracting attention. They are training evaluation, the role of motivation in training, and the use of computer technology in training.
The use of training is often a knee-jerk reaction to a variety of organizational problems. For example, sexual harassment charges in the military have resulted in the addition of a training module to help deal with harassment issues. Unfortunately, the mere implementation of a training program is usually the only evaluation measure used. An adequate evaluation process should specifically assess the extent to which the training program had the intended effects. This approach places greater emphasis on clearly articulating the training objectives prior to the design and implementation of the training. Evaluation measures can then be developed based on these objectives.
Traditional evaluation measures have tended to follow Kirkpatrick's typology, which includes learning, behavior, reactions, and results. Of these, the most common measure has been reactions or trainee evaluations of the usefulness and enjoyment of the training program (sometimes called Happy Sheets). Although useful, this typology has recently been updated in an attempt to further define learning measures to include affective, cognitive, and skill-based indicators of learning. For example, the intended outcome of a course in statistics may be, in addition to learning a number of procedures (e.g., t-tests), to teach students the relationships among the various procedures. In this case, a traditional knowledge test may be deficient. A recently developed approach involves measuring a student's cognitive representation of the concepts using a technique such as the Pathfinder and comparing it with an expert's model. Thus, a successful training program would be one that results in a closer match between student and expert mental models.
Another recent approach to training evaluation uses cost-accounting techniques to evaluate the utility of implementing a training program. The aim of this approach is to change the perception of training as a cost to that of an investment. By using information from well-conducted evaluation studies, return on investment estimates can be developed. Decision makers can then determine whether the organization should invest in upgrading equipment or in upgrading employee skills, for example.
Historically, training research has focused on identifying the conditions that best promote learning. Early research focused on issues such as identical elements, massed vs. spaced practice, and advanced organizers. However, recent research has begun to examine the role of the trainee in the training process.
Perhaps it is obvious that the most advanced training program is doomed to fail if trainees are not motivated to learn the material presented. It is only recently, however, that researchers have begun to take a systematic look at the role of motivation in training.
Some researchers have taken an expectancy approach to motivation by focusing on the linkage between the training material and the trainee's job and career advancement. Thus, motivation to learn is improved by drawing a clear linkage between the training course content and the job content as well as by linking training with rewards and advancement. In fact, a number of organizations have instituted pay-for-knowledge programs in which employees' pay is tied to their accumulation of skills in a variety of areas.
Other researchers have used a social-cognitive approach to study motivation in training. Specifically, the role of self-efficacy beliefs and factors that affect these beliefs have been the subject of a growing number of studies. In general, the research findings support a linkage between self-efficacy and training outcomes such as learning.
Training has also been shown to increase self-efficacy levels, creating a self-perpetuating loop in which high self-efficacy leads to better training performance, and high training performance leads to higher levels of self-efficacy. Because of this situation, studies have begun to examine factors affecting pretraining self-efficacy that can be manipulated in order to increase training outcomes.
For example, in some of my research, I have found that the way in which training assignments are framed can affect pretraining self-efficacy and subsequent learning. Trainees can be told that they are going to training because they are deficient in a particular skill (e.g., basic arithmetic) and are being assigned to a remedial course. On the other hand, trainees may be told that they are going to training to advance their skills beyond their current levels. My research, as well as that of others, suggests that this sort of framing manipulation can influence trainees' attitudes and motivation going into the training program and result in different levels of learning and performance.
In addition to motivation during training, some researchers have examined the motivation to attend training in the first place. This is particularly important in organizations where the responsibility for updating one's skills is left up to the individual (such as in many engineering organizations). These studies have identified a number of organizational (e.g., support and climate) and individual (e.g., motivation) factors that are related to participation in updating activities including formal training courses. As organizations move toward a continuous learning philosophy, this line of research will become even more important.
CD-ROM, virtual reality, and artificial intelligence are all technologies that are revolutionizing the field of training. Training developers are designing multimedia computer software that adapts to the learner's skill level and custom-tailors instructional materials. Although this idea is not new (programmed instruction has been around for some time), the sophistication achieved by these new technologies is unprecedented. Technologies such as virtual reality allow for the design of a high-fidelity training environment for tasks in which actual practice may be too costly or dangerous.
Computer technology is also revolutionizing the way we think about training. Instead of going to a classroom to get instruction that may or may not be relevant to a trainee's current task, developers are beginning to embed training within the task. This approach can be considered a 'training on demand' system in which a piece of software, for example, will recognize a user making the same mistake repeatedly and will flash a quick training module on the screen aimed specifically at that mistake.
Perhaps the most influential technological development of our times is the Internet or the so called Information Superhighway. The Internet's ability to connect people from all over the world and transfer vast amounts of text- and graphics-based information makes it a potentially powerful tool for conducting training. Some universities are currently conducting classes over the Internet, and similar uses by private industry cannot be very far behind. A potential problem, however, is that organizations may begin to conduct training over the Internet just because they can and not because it is the best way to achieve specific training objectives.
The pace of technological advances continues to accelerate at a feverish pace. However, the research base necessary for evaluating the usefulness of these technologies has lagged behind. Developers are often seduced by the technology and forget to measure the extent to which trainees are actually learning anything. Typically, evaluation consists of determining whether or not the system (e.g., software) actually works without any bugs. This is not to say that advances in technology can't lead to better training design. What it does mean is that researchers must establish partnerships with developers in order to harness the true potential of these technologies for delivering training material.
The need for training is likely to increase even more as organizations struggle to keep up with technological advances and world competition. The concept of lifetime employment in an organization is no longer a reality (if it ever was). Thus, individuals will have to take more responsibility for upgrading their skills to match those needed by the marketplace. Psychological science has much to offer the field of training. Now more than ever, we need solid empirical research to guide training practices.