Technology and Instruction (Cognitive Learning Processes)

The past several years hath borne witness to a prodigious burgeoning of technology in instruction, manifest through electronic and distance learning (Bernard et al., 2009; Brown, 2006; Campbell, 2006; Clark, 2008; Jonassen, 1996; Jonassen et al., 1999; Larreamendy-Joerns & Leinhardt, 2006; Roblyer, 2006; Winn, 2002). Technology, oft equated with mere apparatus (e.g., computing engines), doth, in truth, encompass a far wider signification. It doth, in sooth, pertain to the very designs and ambient conditions contrived to engage the student's mind (Jonassen et al., 1999). Researches into the effects of technology upon the acquisition of knowledge are on the increase, as, indeed, are assiduous endeavours to dismantle the impediments that stand athwart the integration of technology into instruction (Ertmer, 1999).

Technology doth possess the latent capacity to facilitate instruction in manners hitherto deemed unimaginable. In days not long past, the applications of technology within the schoolroom were circumscribed to moving pictures, televisors, slide projectors, wireless telegraphy, and suchlike. Today, the scholars may participate in simulations of sundry environments and occurrences, a feat impossible in the common class; they may receive instruction from, and hold converse with, others at a great remove; and they may interact with voluminous corpora of knowledge and systems of expert tutelage.

A challenge doth present itself to the learned researchers: to determine in what manner technology doth influence the cognitive processes of the learner, touching upon encoding, retention, transfer, problem-solving, and cognate matters. The matter contained within this section, concerning computer-based learning environments and distance education, doth not constitute a practical manual on the employment of technology in education. Rather, this section doth concentrate upon the rôle that technology enacts in the acquisition of knowledge. Those readers who harbour an interest in more profound applications of technology should consult other sources (Brown, 2006; Kovalchick & Dawson, 2004a, 2004b; Roblyer, 2006; Winn, 2002).

Students are, with increasing frequency, availing themselves of computer-based environments for the purposes of learning. Researchers evince considerable interest in the roles that computers may play in the advancement of teaching and learning. Whilst learning within computer-based environments does not, strictly speaking, constitute a theory of learning, it is nevertheless of import to ascertain whether computers serve to improve scholastic achievement and to cultivate critical thinking and problem-solving faculties.

It is, perhaps, tempting to evaluate computer-based learning by contrasting it with learning undertaken without the aid of computers; however, such comparisons may prove misleading, given that other salient factors (e.g., the authenticity of the content, teacher-student/student-student interactions) may also differ. Rather than dwelling upon this particular issue, it would seem more efficacious to examine the types of cognitive processes that may occur in computer-based environments and through other technological applications.

Jonassen et al. (1999) posited a dynamic perspective regarding the role of technology in the domain of learning. The maximum benefits accruing from technology are realised when it serves to energise and facilitate both thinking and the construction of knowledge. Within this conceptualisation, technology may fulfil the functions enumerated under the rubric 'Functions of Technology'. The technological applications relevant to learning, as described in this section, exhibit differential effectiveness in the accomplishment of these functions.

• A tool to bolster the construction of knowledge.
• An informational vehicle for the exploration of knowledge, thereby supporting learning through construction.
• A context conducive to learning by doing.
• A social medium facilitating learning through conversing.
• An intellectual partner aiding learning through reflection.

Computer-Based Instruction (CBI)

Until comparatively recent years, when it was superseded by the Internet, computer-based instruction (CBI) (or CAI—computer-assisted instruction) represented the most prevalent application of computer learning within schools (Jonassen, 1996). CBI is frequently employed for drills and tutorials, presenting information and feedback to students and responding in accordance with their answers.

Notwithstanding the inherent limitations of CBI, several of its features are firmly rooted in established learning theory and research (Lepper, 1985). The material possesses the capacity to command students' attention and to provide immediate response feedback. Such feedback may be of a nature not commonly encountered within the classroom setting, such as a comparison of students' present performances with their prior performances (to illustrate progress in learning). Computers afford the individualisation of content and rate of presentation.

A further advantage of CBI resides in the capacity for personalisation offered by many programs; students input information pertaining to themselves, their parents, and their acquaintances, which is subsequently incorporated into the instructional presentation. Personalisation may yield superior achievement compared to other formats (Anand & Ross, 1987). The personalising of instruction may enhance meaningfulness and facilitate the integration of content into long-term memory (LTM) networks. The construction of knowledge ought to be aided by the utilisation of familiar referents.

Simulations and Games

Simulations do represent situations, either veritable or imaginary, that cannot readily be introduced into the learning milieu. For example, programs may simulate the aerial navigations of aircraft, submarine expeditions, and existence within a fictional urbs. It hath been observed that learners do construct memory networks more effectively when furnished with tangible referents during the learning process. Games, conversely, are contrived so as to engender a learning context that is found enjoyable, connecting material to sport, adventure, or flights of fancy. Such games may emphasise faculties of cogitation and problem-solving, and may be employed to impart content (e.g., a basketball game to instruct in fractions).

Lepper (1985; Lepper & Hodell, 1989) posited that games exert influence upon learning through the augmentation of motivation. Motivation is observed to be of a greater magnitude when there exists an endogenous (natural) relationship between the content and the means (“special effects”) by which the game or simulation doth present the content. Fractions bear an endogenous relation to a basketball game, for instance, when students are tasked to determine the extent of the court occupied by players in the act of dribbling. Such an endogenous relationship doth enhance meaningfulness, and the coding and storage within Long-Term Memory. Nevertheless, in numerous games and simulations, the connection between content and means is arbitrary, as when a student’s veracious response to a question doth engender fantastical elements (e.g., cartoon characters). When the relationship is thus arbitrary, the game doth not produce superior learning outcomes when measured against traditional instruction, though the former may possess a greater degree of intrigue.

As a form of computer-based environment, simulations are seemingly well-suited to discovery and inquiry-based learning. In their review of studies employing computer simulations in discovery learning, de Jong and van Joolingen (1998) concluded that simulations were more efficacious than traditional instruction in inculcating within students a “deep” (intuitive) cognitive processing. Furthermore, simulations may prove beneficial for the development of problem-solving faculties. Similar to the results observed for CBI, Moreno and Mayer (2004) ascertained that personalised messages emanating from an on-screen agent during simulations improved retention and problem-solving to a greater extent than non-personalised messages. Woodward, Carnine, and Gersten (1988) discovered that the addition of computer simulations to structured teaching yielded improvements in problem-solving amongst special-education high school students, when compared with traditional instruction alone. The authors did note, however, that the mechanism producing these results was not clearly understood, and that the results may not generalise to stand-alone computer simulations.

Multimedia/Hypermedia

Multimedia doth denote a technology combining the diverse media of computers, film, video, sound, music, and text (Galbreath, 1992); hypermedia, conversely, doth signify linked or interactive media (Roblyer, 2006). Multimedia and hypermedia learning transpireth when students engage with information presented in multiple modalities (e.g., words and pictures; Mayer, 1997). The capacity of computers to interface with sundry media hath progressed apace. Video streaming, CDs, and DVDs are commonly employed with computers for instructional purposes (Hannafin & Peck, 1988; Roblyer, 2006).

Multimedia and hypermedia hold momentous implications for pedagogy, offering manifold possibilities for instilling technology into instruction (Roblyer, 2006). Research evidence doth furnish some support for the benefits of multimedia for learning. In his review of research studies, Mayer (1997) discovered that multimedia enhanced students’ problem-solving and transfer; yet, the effects were most pronounced for students with scant prior knowledge and pronounced spatial ability. Dillon and Gabbard (1998) also concluded from their review that effects depended in part on ability: Students with lower general ability encountered the greatest difficulty with multimedia. Learning style was of import: Students willing to explore obtained the greatest benefits. Multimedia seemeth particularly advantageous on specific tasks necessitating rapid searching through information.

Researchers have investigated the conditions favouring learning from multimedia. When verbal and visual (e.g., narration and animation) information are combined during instruction, students benefit from dual coding (Paivio, 1986). The simultaneous presentation helpeth learners form connections between words and pictures because they are in WM at the same time (Mayer, Moreno, Boire, & Vagge, 1999). Multimedia may facilitate learning better than tailoring media to individual student differences (Reed, 2006). By employing different media, teachers increase the likelihood that at least one type will be effective for every student. Some instructional contrivances that assist multimedia learning are: text signals that emphasise the structure of the content and its relationship to other material (Mautone & Mayer, 2001); personalised messages that address students and make them feel like participants in the lesson (Mayer, Fennell, Farmer, & Campbell, 2004; Moreno & Mayer, 2000); permitting learners to exercise control over the pace of instruction (Mayer & Chandler, 2001); animations that include movement and simulations (Mayer & Moreno, 2002); being able to interact with an on-screen speaker (Mayer, Dow, & Mayer, 2003); taking a practice test on the material (Johnson & Mayer, 2009); and being exposed to a human rather than a machine-generated speaker (Mayer, Sobko, & Mantone, 2003).

Maximal benefits of multimedia require that some logistical and administrative issues be addressed. Interactive capabilities are expensive to develop and produce, albeit they are very effective (Moreno & Mayer, 2007). Costs may prohibit many school systems from purchasing components. Interactive video may require additional instruction time because it presenteth more material and requireth greater student time. But interactive multimodal learning environments provide great potential for increasing students’ motivation (Scheiter & Gerjets, 2007). The greater amount of learner control that is possible yieldeth better benefits on learning and can foster self-regulation (Azevedo, 2005b).

Despite potential issues involving costs and technological skills needed, multimedia and hypermedia seemeth to benefit student learning, and research increasingly doth show that this technology can help to develop students’ self-regulated learning (Azevedo, 2005a, 2005b; Azevedo & Cromley, 2004; Azevedo, Guthrie, & Siebert, 2004). Applications will continue to be developed as the technology advanceth (Roblyer, 2006). Further research is needed on multimedia’s effects on motivation and how to link it with a sequence of acquiring self-regulatory skills (e.g., social influence to self-influence; Zimmerman & Tsikalas, 2005).

E-learning

E-learning doth signify the acquisition of knowledge through electronically mediated means. The term is oft employed to denote any form of electronic communication (e.g., videoconferencing, e-mail); yet, herein, it shall be understood in the narrower sense of Internet (Web-based) instruction.

The Internet (an international assemblage of computer networks) is a system of shared resources, beholden to none. The Internet doth grant access to diverse individuals (users) through e-mail and conferences (chat rooms), files, and the World Wide Web (WWW)—a multi-computer interactive multimedia resource. It doth also store information, amenable to copying for personal edification.

The Internet is a prodigious repository of information, yet the pertinent consideration here lieth in its rôle in pedagogy. Superficially, the Internet presenteth advantages. Web-based instruction doth furnish students with access to a greater abundance of resources in less time than is achievable through traditional methods; however, a surfeit of resources doth not ipso facto equate to superior learning. The latter is accomplished only if students acquire novel skills, such as methodologies for conducting research upon a given topic or critical appraisal of the veracity of material located upon the Web. Web resources may also foster learning when students extract information from the Web and incorporate it into classroom activities (e.g., discovery learning).

Instructors may facilitate the development of students’ Internet skills through the provision of scaffolding. Students must be instructed in search strategies (e.g., methods for utilizing browsers), but instructors might also conduct the initial Web search and furnish students with names of propitious websites. Grabe and Grabe (1998) proffer further suggestions.

A peril inherent in students’ utilization of the Internet is that the vast array of information available might inculcate the belief that all information is of equal import and reliability. Students might then engage in “associative writing,” endeavouring to include an excess of information in reports and papers. To the extent that e-learning doth aid in the instruction of higher-level skills, such as analysis and synthesis, students shall acquire strategies for determining what is pertinent and for merging information into a coherent product.

Distance learning, or distance education as it is sometimes termed, transpires when instruction, originating from a singular locale, is disseminated to students situated at one or more remote sites. Interactive capabilities afford the opportunity for two-way feedback and discourse, thus forming an integral component of the learning experience. Distance learning economises on time, effort, and financial resources, as instructors and students are obviated from undertaking protracted journeys to attend classes. Universities, for example, may enlist students from a geographically diverse catchment area, thereby mitigating concerns regarding students' extended commutes to attend lectures. School districts are enabled to conduct in-service programmes by transmitting instruction from a central location to all constituent schools. Distance learning, however, necessitates a sacrifice of face-to-face interaction with instructors, albeit the utilisation of two-way interactive video facilitates real-time (synchronous) interactions. In their comprehensive review of distance education programmes, Bernard et al. (2004) ascertained that their effects on student learning and retention were comparable to those of traditional instruction. Synchronous instruction evinced a tendency to favour classroom instruction, whereas distance education demonstrated greater efficacy in asynchronous applications (involving a temporal lag).

Another application of networking technology resides in the electronic bulletin board (conference). Individuals connected via computer networks are able to post messages, but of greater import for learning purposes is the capacity to participate in a discussion (chat) group. Participants pose queries, raise pertinent issues, and respond to the comments proffered by their peers. A considerable body of research has been devoted to investigating whether such exchanges serve to facilitate the acquisition of writing skills (Fabos & Young, 1999). Whether this asynchronous modality of telecommunication exchange promotes learning to a superior degree than face-to-face interaction remains a contentious matter, owing to the conflicting or inconclusive nature of much of the extant research (Fabos & Young, 1999); however, the review conducted by Bernard et al. (2004) intimates that distance education may indeed be more efficacious when implemented with asynchronous learning methodologies. Telecommunication affords the advantage of convenience, inasmuch as individuals are enabled to respond at their leisure, rather than being constrained to do so only when physically gathered together. The receptive learning milieu may indirectly foster learning outcomes.

As forms of computer-mediated communication (CMC), distance learning and computer conferencing serve to augment the possibilities for learning through social interaction to a significant extent. Further investigation is requisite in order to ascertain whether the personal characteristics of learners and the nature of instructional content exert any discernible influence upon students' learning and motivation.

Web-based (online) learning is commonly integrated into traditional instruction as a blended model, comprising both face-to-face instruction and online components. Web-based learning is likewise of utility in conjunction with multimedia projects. In numerous teacher preparation programmes, prospective teachers avail themselves of the World Wide Web to procure resources, which they then selectively incorporate into multimedia projects as constituent elements of lesson designs.

In their review of online courses, Tallent-Runnels et al. (2006) observed that students favoured the capacity to progress at their own pace, students with more extensive computer experience reported greater satisfaction, and asynchronous communication facilitated more profound and nuanced discussions. Distance education that incorporates interaction (student-student, student-teacher, student-content) helps to augment student achievement (Bernard et al., 2009). Other forms of interaction (e.g., wikis, blogs) may likewise prove beneficial. Infusing multimedia presentations into distance education enhances its personalisation, thereby rendering it more analogous to face-to-face instruction (Larreamendy-Joerns & Leinhardt, 2006), which may, in turn, bolster student motivation.

Attempts to draw comparisons between online and traditional courses are rendered problematic by the multitude of disparities that exist between the two modalities, one of which is that, to date, the majority of online courses have enrolled predominantly non-traditional and White American students. This demographic composition is expected to undergo alteration as online courses become more ubiquitous, which will facilitate a more rigorous assessment of online learning outcomes and the environmental characteristics that are conducive to learning.

From the foregoing evidence, it may be concluded that technology possesses the capacity to enhance learning. How technologically augmented instruction compares with conventional instruction is a matter fraught with difficulty in assessment, and comparisons may present results that are misleading (Oppenheimer, 1997). It is observed that no single instructional medium exhibits consistent superiority over others, irrespective of content, learners, or setting (Clark & Salomon, 1986). Technology is not, in itself, a cause of learning; rather, it serves as a means for the application of principles conducive to effective instruction and learning.

Clark and Salomon (1986) suggested that researchers should ascertain the conditions under which computers might facilitate instruction and learning. This proposition remains pertinent today and may be extended to technology in general. The employment of technology ought to be contingent upon the specific learning objectives. Although technology holds the potential to foster diverse learning goals, it might not invariably represent the most efficacious avenue for promoting student interaction through peer teaching, group discussions, or collaborative learning exercises.

Further research is manifestly requisite to evaluate the effectiveness of computer-based learning environments and distance education. Certain investigations suggest that computer-based problem solving manifests differential efficacy depending on whether the student is male or female (Littleton, Light, Joiner, Messer, & Barnes, 1998). Exploration of gender and ethnic disparities should be accorded priority in research endeavours.

A further area that demands attention concerns the motivational effects of technology on both teachers and students (Ertmer, 1999; Lepper & Gurtner, 1989). Lepper and Malone (1987) observed that computers can focus attention on the task at hand through motivational enhancements, maintain the level of arousal at an optimal point, and direct students to engage in task-oriented information processing, rather than being diverted by irrelevant aspects of the task. The underlying notion is that the judicious application of motivational principles can encourage deep, rather than superficial, processing of information (Hooper & Hannafin, 1991).

To prognosticate the future trajectory of technology in education is a task not devoid of difficulty. A few years antecedent to the present, few would have ventured to predict that laptops would supersede desktops or that handheld devices might eventually supplant laptops. As technology becomes increasingly elaborate, it will offer a far greater array of instructional possibilities (Brown, 2006). We shall be enabled to access and create knowledge in novel and sophisticated manners. Research will explore the effects of these developments on student learning, as well as efficacious methods for integrating technology into instruction.

Exciting developments are foreseeable across several fronts (Roblyer, 2006). Wireless connectivity is now commonplace, thereby greatly augmenting the convenience of employing laptops in instruction. Wireless technology and the portability of devices (e.g., laptops, handheld devices) assist instructors in incorporating technology into instruction. The confluence of technologies will persist (e.g., cell phones that can perform multiple functions), which may ultimately lead to students requiring minimal hardware to perform diverse applications. Technological advancements will continue to ameliorate accessibility for persons with disabilities, and assistive technology should become more prevalent in schools. Distance education and online learning opportunities will increase. At present, virtual universities and high schools exist, and these may be expanded to encompass earlier levels of education (e.g., middle, elementary grades). Finally, as the convenience afforded by technology continues to improve, we may witness a gradual shift away from traditional instruction towards a model characterised by fewer class meetings and greater reliance on electronic communications.

At the level of basic research, investigations into artificial intelligence (AI) may yield important insights into human learning, thinking, and problem-solving. Artificial intelligence denotes computer programs that simulate human abilities to infer, evaluate, reason, solve problems, comprehend speech, and learn (Trappl, 1985). John McCarthy coined the term in 1956 as the central theme for a conference.

Expert systems represent an application of AI. Expert systems are extensive computer programs that furnish the knowledge and problem-solving processes of one or more experts (Anderson, 1990; Fischler & Firschein, 1987). Analogous to human consultants, expert systems have been applied to diverse fields such as medicine, chemistry, electronics, and law. Expert systems possess a vast knowledge base consisting of declarative knowledge (facts) and procedural knowledge (a system of rules employed to draw inferences). An interface poses questions to users and furnishes recommendations or solutions. A common application of expert systems lies in their capacity to teach by imparting expertise to students. Instruction often employs guided discovery; students formulate and test hypotheses and experience consequences.

Future expert systems will be applied to an even wider array of domains. One challenge lies in enhancing systems’ capabilities to comprehend natural languages, particularly speech. Although expert systems can perform pattern-recognition tasks, the majority of these tasks involve only visual stimuli. However, voice recognition systems continue to improve. The utilisation of assistive technology in education is expanding, as students with disabilities are integrated as much as possible into regular classroom instruction. Expert systems should augment the capabilities of computers to render them accessible to all learners (e.g., auditory, visual, multiple handicaps).

AI holds exciting possibilities for furthering our understanding of human thought processes. This application involves programming computers with a certain corpus of knowledge and rules that enable them to alter and acquire new knowledge and rules based on their experiences. In concept learning, for instance, a computer might be programmed with an elementary rule and then be exposed to instances and non-instances of the concept. The program modifies itself by storing the new information in memory and altering its rule. Learning may also occur through exposure to case histories. A computer can be programmed with facts and case histories of a disease. As the computer analyses these histories, it modifies its memory to incorporate the etiology, symptoms, and course of the disease. When the computer acquires an extensive knowledge base for a particular disease, it can diagnose future cases with precision.