AIR FORCE RESEARCH INSTITUTE

Maxwell Air Force Base, Alabama

Leveraging Affective Learning for 

Developing Future Airmen

Donald Tharp

Colonel, USAF

Dr. Anthony Gould

Robert Potter

Colonel, USAF, Retired

November 2009

R esearch S tudy
ii

Disclaimer

Opinions, conclusions, and recommendations expressed or implied within are solely those of the 

authors and do not necessarily represent the views of the Air Force Research Institute, Air University, the United States Air Force, the Department of Defense, or any other US government agency. 

Cleared for public release: distribution unlimited.


Leveraging Affective Learning

for Developing Future Airmen

The mission of Air Education and Training Command (AETC) 

is to empower our nation’s Airmen to fly, fight, and win by 

“delivering unrivaled air, space, and cyberspace education and 

training.” However, realizing this vision in today’s highly interactive, information-saturated, and global environment is tougher 

than ever. Mission success requires knowledge-enabled Airmen 

who understand, appreciate, trust, and internalize the tactics, 

techniques, processes, and procedures necessary to succeed in 

any number of complex situations.

As leaders at all levels, our Airmen must be able to anticipate 

and appropriately respond to a complicated and fluid national 

security environment. Developing such Airmen will require 

stronger commitments to education and training on the part of 

the learner to the point where learning never stops. Fostering 

this highly favorable attitude toward learning is possible only if 

Air Force education and training programs address learners’ 

goals, motivations, social interactions, and individual learning 

styles. This means the Air Force needs a stronger focus on 

affective learning during the instructional design (ID) process 

for education and training.

The ability to handle complex problems across a wide spectrum of missions is not acquired through traditional rotelearning practices that merely assess an individual’s ability to 

memorize facts in the short term. Air Force learning processes 

must facilitate intuitive understanding and personal internalization of often conflicting concepts, applications, and decisionmaking models. Effective education and training methods must 

recognize the filters and perceptions individuals will employ to 

frame a solution to any number of problem sets. Relying solely 

on a cognitive learning approach for leadership development is 

quickly being eclipsed by a drive to understand and employ 

affective methods to enhance learning and internalize decisionmaking skills (Beard & Smith, 2007).

Recognizing the evolutionary changes in the information environment, AETC published a white paper entitled On Learning: 

The Future of Air Force Education and Training (2008), which 
stipulates that successful education and training in today’s 

complex environment require a new learning culture. This includes instant and unfettered access to information through 

knowledge management, nonstop learning opportunities to provide continuous learning, and the right information at the right 

time that leads into precision learning. However, in addition to 

flexible and timely access to information, an effective Air Force 

learning environment must also instill in every Airman a strong 

desire to learn continuously.

More than just the opportunity and means to learn, effective 

education and training also require engendering students’ desire to improve continuously (Weiner, 1986). This should be directed at improving abilities and knowledge to accomplish the 

mission more effectively. A large percentage of the academic 

failure rate in our nation’s schools is not because of limited 

facilities or incompetent teachers. Rather, many students fall 

behind because they do not feel that learning is important to 

them (Lemke, 2003). To ensure mission success, the Air Force 

must have education and training programs that consider not 

only cognitive goals, but also learners, attitudes, and motivations. This should be carried out through the use of expert ID 

and innovative technology applications that inspire students to 

put forth their best effort.

Because of the fast-changing, technology-driven environment in which we operate, a true warrior ethos must be dominated by a desire to learn (AETC, 2008). This paper addresses 

the importance of instilling that desire through Air Force education and training, and it examines various ways that technology can help. The opening portions of this paper review general 

learning theory, including the cognitive and affective aspects of 

learning. The next section considers the impact of ID on cognitive and affective learning. Good ID is the primary means to 

engage the affective domain. The paper then considers how 

technology can facilitate cognitive and affective learning processes. Recent advances in technology provide increased social 

networking and adaptive learning applications that cater to affective needs. The remaining sections discuss how to apply 

these concepts with regard to advanced technologies, leadership, and future research.
Learning Domains

Learning can be viewed as both a product and a process. 

Standard definitions of learning from the educational psychology 

textbooks of 40 years ago generally defined learning as a 

“change in behavior as a result of experiences” (Twigg, 1994). 

This behaviorist approach assessed learning as an outcome 

that resulted in some external behavioral activity; however, not 

all learning leads to overt behavior. Consequently, many theorists later refined the definition of learning to consider changes 

in the way people “understand, or experience, or conceptualize 

the world around them” (Ramsden, 1992). So learning is an increase in information, but it also involves interpreting and comprehending. Different learners filter information in different 

ways, based on perspective. Individuals then restructure information to create personal knowledge (Ramsden, 1992). In other 

words, learning is a multidomain process involving intellect, 

emotion, and physical skills. Further, these domains are connected, and the condition of one influences the others.

Historically, educators have recognized and accepted the notion of separate domains for addressing different types of learning objectives. Bloom and his group’s (1956) foundational effort 

established three categories or domains of educational objectives and identified them as cognitive, psychomotor, and affective. The theory and accompanying research for the cognitive 

(thinking) and psychomotor (physical) categories are fairly well 

defined and commonly accepted. The definition and theoretical 

framework of the affective category has been more problematic 

and difficult to establish. This lack of clarity exists because the 

affective domain concerns human cultural beliefs, behaviors, 

attitudes, motivations, feelings, perceptions, and emotions that 

are very fuzzy and lead to ill-defined characterizations. Each of 

the three domains requires specific considerations, based on 

the intended learning objectives (Main, 1992).

Cognitive Domain

Processes involving the development of intellectual skills characterize the cognitive domain. According to Bloom (1956), the 

cognitive domain is best described by six categories that typify 

successive levels of thought complexity. Knowledge, comprehen-
sion, application, analysis, synthesis, and evaluation designate 

progressive stages ranging from recalling simple information to 

making judgments about the value of ideas or concepts. Collectively, the theoretical range of the cognitive domain connects the 

thought processes necessary to acquire, process, and interpret 

information. This linkage to information processing makes computers and associated information technology applicable, facilitating cognitive objectives (Jonassen & Carr, 2000).

The most effective educational processes in the cognitive domain challenge and support the learner’s ability to grasp new 

information and concepts. They focus on knowledge, reasoning, and performance that underpin the categories in Bloom’s 

taxonomy (Krathwohl, 1964). Assessment processes in the cognitive domain determine the level of understanding achieved 

and provide feedback on learning outcomes. Educators design 

lessons intended to maximize the transfer of information and 

provide valid learning-assessment tools. Most educational programs focus almost exclusively on these processes during ID 

(Pierre & Oughton, 2007).

Psychomotor Domain

The psychomotor domain involves physical movement, coordination, and the use of motor skills and is generally associated with training. Physical skills, developed through training 

or practice, are measured in terms of accuracy, speed, precision, distance, or technique. There are several taxonomies describing psychomotor skills, and each includes increasing levels 

of physical dexterity and ability to adapt new movements when 

necessary. This domain is considered well defined as the results 

from empirical research generally agree with theories concerning psychomotor learning (Bloom, 1956). Pilot, vehicle driver, 

weapons operator, and maintainer training are examples of 

psychomotor instruction.

Affective Domain

Processes involving our needs and emotions characterize the 

affective domain. Affective filtering of life’s circumstances creates an individual’s disposition, enthusiasm, motivation, attitude, attention, value, and emotion regarding another individ-
ual, object, fact, concept, process, and/or belief. Sinclair (1985) 

refers to affect as a term used to describe the feeling or emotional aspect of experience, associated with

• the motivation of behavior,

• the maintenance and enhancement of self-esteem in the 

educational setting,

• anxiety and achievement motivation,

• development of curiosity and a need to know and understand, and

• social motives, such as a need for praise, recognition, and 

attention.

Although affective learning is difficult to define, anyone who 

has taught for very long recognizes its crucial role. In any given 

lesson, some students seem driven to absorb new concepts and 

ideas while others seem disinterested. This situation can lead to 

the often-heard phrase “what is taught is not the same as what 

students learn” (Atherton, 2005). This highlights the strong 

influence exerted by affective processes on cognitive learning. 

Though theoretically incomplete, empirical evidence suggests that 

the absence of affective internalization of a concept attenuates 

long-term learning (Rose & Meyer, 2002). Restated more simply, 

students who have little desire or interest to learn will learn 

little. Unfortunately, due to the indistinct nature of the affective 

domain noted above, there is not a good theoretical model for 

predicting the precise impact of affect on learning. A systematic 

approach for detecting level of affect is needed to assist teachers 

as they try to motivate and involve their students.

Several schemas have been proposed to describe the processes 

of the affective domain. Krathwohl (1964) proposed the most widely 

cited taxonomy with five major categories describing levels of affect. These categories, listed below in order from lowest to highest 

affect, provide a rough framework to assess and compare:

1. Receiving—Passive attention to phenomena (e.g., listens 

attentively, asks, sits erect, and identifies).

2. Responding—Active participation in and reaction to phenomena (e.g., participates, discusses, and helps others).
3. Valuing—Attachment of worth to phenomena (e.g., explains, proposes, shares, and differentiates).

4. Organizing—Construction of value system that compares 

and relates phenomena (e.g., generalizes, integrates, and 

synthesizes).

5. Characterizing by value—Application of consistent value 

system to control characteristic behavior (e.g., works independently).

This taxonomy and its full description provide enough detail to 

create learning objectives that address the affective domain. The 

following is an example of an affective learning objective used 

many years ago by the Air Force Academic Instructor School:

The objective of this lesson is for each student to respond positively to 

using reflective teaching techniques to improve teaching ability.

Forty years ago, educators placed nearly as much emphasis 

on affective objectives as they did on cognitive objectives (Krathwohl, 1964). Since that time, the share of affective objectives in 

ID has slowly declined to the point that few schools today include affective objectives in their lessons.

A student’s affective state influences his or her learning predisposition, and educators should consider this when designing and developing education and training courses. Students 

use affect as a filter to assist them in developing attitudes about 

the course, the instructor, their peers, and the topic that in turn 

contributes to students’ overall success in the learning process 

(Jolivette, 2006). When it comes to mastering skills, it is essential for students to exercise cognitive processes, but effective 

cognitive retention is marginalized if the affective domain is 

ignored. If one feels threatened, sad, bored, stressed, or preoccupied, the learning process can break down (Griffith & Nguyen, 

2006). Instructional theories and design models focus on the 

cognitive and psychomotor domains. Research generally makes 

the obligatory mention of the affective domain, but in practice 

affect is largely ignored as an area of scientific study in the 

instructional-technology field.

There are numerous reasons proposed to explain why affective objectives are seldom included in the curriculum of most 

schools (Krathwohl, 1964; Martin & Briggs, 1986):
 1. Affective results are long range and intangible.

2. People fear the perception of brainwashing (blurring of 

education and indoctrination).

3. Outcomes can be “faked.”

4. Assessment is subjective (self-reported observations).

5. Absence of behaviors is as important as presence.

6. Some persuasive communication methods cause uneasiness.

7. Definition and understanding of affect are imprecise.

8. People disagree about affective behavior outcomes.

9. Using computers to teach attitude seems Orwellian.

10. The goal is efficiency, so affect is easily excluded.

Each of these factors has contributed to the limited use of affective learning objectives. However, another factor that may have 

played a role was the growing influence of technology on education (Achacoso, 2003). During the past half century, technology 

has grown ever-more present in the educational process. Computers, networks, multimedia, the Internet, online communication, and all forms of digitized information are commonly termed 

educational technology (Ed Tech) when employed for learning. 

Ed Tech has revolutionized the educational environment, and 

few classrooms are without some level of Ed Tech in place.

Impact of Technology

Technology has routinely influenced educational theories, 

and some models of thinking reference the human mind in 

terms similar to a computer (Robertson, Elliot, & Robinson, 

2007). The senses are seen as input devices, memory as a database, and the brain as some type of microprocessor. This may 

be a useful construct when considering presentation and recall 

of information, but one of the drawbacks to this type of model is 

that it neglects many other human processes such as interest, 

attention, emotion, beliefs, and motivation. Consequently, the 

impact of these factors on learning, which are frequently referred 

to as affective qualities, has often been ignored.
Advances in Ed Tech generally mirror advances in the broader 

technological realm, which has been dominated by software and 

hardware focused on efficiently delivering and transferring information. Over the past 40 years, educators have focused on 

the efficiencies that technological advances afforded educational processes (Lemke, 2003). Computer-based instruction, 

Internet access, electronic testing, distance-learning applications, television, and content-management systems allow educators to transfer information to students and assess that transfer on a grand scale (Cuban, 1987). The combined effect of these 

initiatives reduced the influence of human emotions on learning. Predominantly, educators ignored the student’s need for 

connection and personal involvement, both of which are necessary for effective learning. This situation created a bias toward 

cognitive objectives, which has only lately begun to subside 

(Griffith & Nguyen, 2006). Recent developments in technology 

may help restore some balance between information processing 

and human involvement.

Paradoxically, technology that in the past may have led to a 

bias in favor of cognitive objectives may now be used to foster 

and scaffold affective objectives (Jolley, Wolfsberger, Rainer, & 

Bell, 2004). Improved networking technologies promise new 

mechanisms for social interaction, and advances in human/

computer interaction are on the threshold of allowing computers 

to recognize user affect and respond accordingly. The latest 

social and communication technologies have led to applications that promote collaboration and student interaction. Educators now recognize that social learning (collaboration) tools 

have the potential to create opportunities to meet both cognitive and affective learning objectives. These tools include discussion forums, blogs, wikis, virtual worlds, and personal Web 

pages. However, the key to employing technology to support 

affective objectives is proper ID, which blends Ed Tech into the 

learning process.

Measuring Affect

Assessing progress in meeting affective learning goals requires more effort than evaluation for cognitive objectives. “Difficulty with measuring affective goals is cited in the literature 
as one of the major reasons for neglecting the affective domain 

in instructional design models” (Main, 1992). Perhaps the most 

important factor in this regard is the protracted period required 

to cultivate complex affective behaviors. Most instructional 

periods are relatively short. Influencing a learner’s value system generally requires instruction over a prolonged period. In 

addition, some affective objectives such as attention usually 

require periodic reinforcement. Main (1992) points to advertising or public relations campaigns as examples that address 

lower-level affective objectives over an extended period.

There are several basic methods for assessing affect. Direct 

behavioral observation is considered the most reliable but may 

not be possible for a large number of students or for dispersed 

learning activity. The ability to discern the affective state of 

students is a vital skill for effective teaching. One-on-one conversations or an interview is another method available to query 

a learner’s affective state. However, workload and personnel 

constraints frequently impede such time-intensive assessment 

methodologies.

Self-reporting is another means to determine a learner’s affective state. Surveys or questionnaires are generally used to query 

attitude or other affective characteristics, but there can be 

problems with reliability. Some students may give the answers 

they believe more suitable rather than express their true emotional state or attitude. Another means to measure overall affective state is an implicit questionnaire designed to reveal affect without bias from the student (Anderson, 2000). These 

instruments probe affective characteristics through a series 

of highly formatted, previously validated questions to register 

affect reliably. Writing assignments are commonly used as a 

valid assessment of affect. Essays can provide evidence of a 

learner’s attitude toward a particular subject. However, analyses 

of essays can be somewhat subjective and may require a rubric 

and trained evaluators (Anderson, 2000).

Instructional Design Process

So how do we bridge the gap and develop linkage between cognitive and affective instruction as we develop lifelong learners? 

The key is to use an integrated ID process that targets both the 
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affective and cognitive domains. According to Smith and Ragan 

(1999), ID refers to the “systematic and reflective process of 

translating principles of learning and instruction into plans 

for instructional materials, activities, information resources, 

and evaluation.” Good ID produces effective lessons based on 

sound educational principles. To be effective, lessons must 

both engage the learner and provide instruction in a clear and 

an efficient manner.

Engaging learners requires instructional designers to focus 

on incorporating the affective domain along with the cognitive 

domain during the ID process. The problem resides with the 

prevalent tendency to use ID models centered on instruction for 

cognitive objectives (Main, 1992). However, the more instructional designers know about both the cognitive and affective 

processes involved in learning, the more competent and confident they are with regard to designing effective learning (Sugrue, 2004). Expert ID of affective objectives can lead to greater 

motivation on a particular lesson and to successful cognitive 

and affective outcomes.

According to Pierre and Oughton (2007), instructional designers should not limit efforts in the affective domain to just motivating students to learn. Rather, they should consider how to 

engage students in deeper learning through the use of affective 

learning with appropriate pedagogy and evaluation methods. ID 

needs to become more effects based by creating instruction that 

addresses teaching strategies and learning outcomes that span 

the various levels of Bloom’s taxonomy. In effects-based design, 

the designer considers holistic effects and the interrelated and 

interdependent nature of the learning domains. Main (1992) 

stated that integrating the affective instructional component 

into, or alongside, the ID model or process ensures that domain 

objectives are covered in every lesson.

The ID process ensures that learning does not occur in a 

haphazard manner but is guided using a process with specific, 

measurable outcomes. The responsibility of the instructional 

designer is to create an instructional experience which ensures 

that learners will achieve the desired learning outcomes. ID 

has the appearance of a linear system; however, it is best viewed 

as an interactive process in which sequencing and fine-tuning 

of objectives are possible. There are no prohibitions against 
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incorporating affective events or making changes to instruction. 

Teachers can adapt instruction based on evaluations and flow 

changes back through the process. Using ID as a working template can create the right learning program or process and justify necessary resources (Piskurich, Beckschi, & Hall, 2000).

The ID process considered for the purpose of this study is the 

Military Instructional System Development (ISD) Model (Branson et al., 1975). Analysis, Design, Development, Implementation, and Evaluation—generically known as ADDIE—is widely 

accepted as an industry standard for ID of educational media 

(Liu, 2008). The ADDIE model brings a generic, systematic approach based on foundations-of-learning principles and standard system theory to the ID process (Tennyson, 1989). The 

ADDIE process provides a framework that instructional designers can use to optimize the effectiveness of instructional products and the efficiencies of creative processes (Hall, 1997).

Each phase of the ADDIE model is a decision-making process that needs to ensure the effectiveness of the instructional 

experience (Smith & Ragan, 1999):

• Analysis: The instructional problem is clarified, the goals 

and objectives are established, and the learning environment and learner characteristics are identified.

• Design: The instructional strategies are designed, the 

media choices are made, and the objectives and tasks that 

will show student mastery are created.

• Development: Materials are produced according to the 

instructional process.

• Implementation: Instruction is tested using prototypes 

(with the targeted audience). Flaws are corrected or revised 

before the product goes into production, and learners and 

instructors are trained on product use. Flexibility is the 

key element during the implementation phase.

• Evaluation: Feedback is gathered to help determine instructional effectiveness. Many consider this the most important 

stage, and it should be an ongoing process.
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Affective or Motivational Design

Motivational design is a systematic process that results in the 

preparation of learning programs that predictably influence the 

learner’s behavior. Consequently, motivational design is concerned with connecting instruction to learner goals, providing 

stimulation and appropriate levels of challenge, and influencing 

how learners will feel following success or failure of goal accomplishment. Every educator understands the challenge of stimulating and sustaining learner motivation and the difficulty of 

finding reliable and valid methods for motivating learners.

One approach to motivational design is provided by Keller’s 

Attention, Relevance, Confidence, and Satisfaction (ARCS) model 

of motivation (Keller 1983, 1999a, 1999b, 2000). The ARCS model 

is based on a synthesis of motivational concepts and characteristics that provide guidance for analyzing the motivational characteristics of a group of learners and then designing motivational 

strategies to fit the learners (Keller, 2000). The four conditions 

that comprise ARCS must be met to motivate learners.

There are two major parts to the model. The first is a set of 

foundational factors representing the components of motivation, based on research into human motivation. The instructional designer should use them as guidelines during lessondevelopment activities:

• Attention strategy relates to stimulating and maintaining 

the learner’s attention by initiating an instructional event 

with some sort of sensory stimuli and/or varying the kinds 

of activities or media.

• Relevance strategy communicates to the learner how the 

activity or event relates to personal needs, interests, or 

motives.

• Confidence strategy relates to the learner’s expectancy to 

feel it is worth the effort to participate in the activity.

• Satisfaction strategy provides extrinsic and intrinsic reinforcement from the learning experience.

The second part of the ARCS model is a systematic design 

process that assists in creating motivational strategies appropriate for a given set of learners. The synthesis allows educa-
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tors to identify the various elements of student motivation; the 

design process helps profile students’ motivational characteristics in a given learning environment and then design appropriate motivational tactics (Keller, 1999b). Keller further breaks 

down each ARCS strategy into three psychological concepts 

that assist designers by providing a theoretical foundation for 

each component:

• Attention—perceptual arousal, inquiry arousal, and variability

• Relevance—goal orientation, motive matching, and familiarity

• Confidence—learning requirements, success opportunities, and personal control

• Satisfaction—intrinsic reinforcement, extrinsic rewards, 

and equity

Combined Instructional and Motivation Design

Keller never intended that the ARCS model stand apart as a 

separate system for ID; rather, it should be incorporated with 

instructional models (Keller & Song, 2001). Additionally, history 

and research have revealed that no one theoretical foundation 

for ID practices is suitable for all applications (Willis & Wright, 

2000). Both affective and cognitive ID approaches account for 

meaningful learning and realistic contexts for application knowledge and skills (Atkins, 1993). Both recognize the importance of 

learner motivation and prior experience (Dick, 1996).

Keller’s ARCS model attempted to correct discrepancies that 

marginalized the efficacy of most educational theories (Main, 

1992). That is to say, while a learner may be motivated toward 

learning, there is no assurance that a person is motivated to 

learn what the instructional event delivers. Additionally, instructional designers cannot assume they understand student motivation. During analysis, designers must attempt to understand how best to encourage students to reach the same conclusions regarding the values, interests, motivation, and content intended by the lesson’s learning objectives (Gunter, 

Kenny, & Vick, 2006). The goal should be a combined ID model 
14

that includes a structured process incorporating both cognitive 

and affective concerns. Main (1992) suggested integrating the 

ADDIE and ARCS models using a matrix to address the two domains in a systematic manner. Integrated ID (Figure 1) is an essential component for building an effective learning program.

The design process has become more complex as advanced 

communication technologies have made social networking, 

information retrieval, and knowledge management available 

24/7 worldwide. To bridge the gap and engage students in 

deeper, meaningful learning, instructional designers need to 

incorporate the affective domain during the design process. 

They must also follow the fundamental principles that apply to 

all pedagogy, including the external conditions that support 

learning and performance (Sugrue, 2004).

A large number of instructional strategies and models are 

available for designers to help facilitate learner engagement and 

the learning process. It is important for instructional designers 

to have a solid understanding of the theory and the design process though they need not be subject-matter experts in a particular discipline. This paradox makes it important for instructional designers to keep sight of what Sugrue (2004) calls the 

five fundamental learning and performance principles:

1. Learning is not performance: Align learning objectives with 

required performance objectives entwined with adequate 

incentives for applying the new skill and knowledge.

Figure 1. Combining ISD and affective-design models
15

2. Medium is not the method: Design to maximize strengths 

of the medium, but don’t expect the medium itself to influence content effectiveness.

3. External and internal conditions should match: Ensure 

that flexible instructional methods are compatible with 

the cognitive processes of acquisition, knowledge storage, 

and retrieval while motivating learners to engage in their 

own learning.

4. Authentic practice makes perfect: Design as contextually 

realistic as possible, matching goals of instruction for 

deepening knowledge.

5. One size does not fit all: Accommodate individual differences by monitoring performance; diagnosing weaknesses; 

and adjusting feedback, information, and practice activities to meet group and/or individual goals.

Instructional designers well grounded in affective and cognitive 

learning and motivation processes are better equipped to design effective learning products.

Learning with Technology

Ed Techs are evolving daily, and the use of advanced Ed 

Techs in the classroom is now the rule rather than the exception. Higher education in the United States has given priority to 

integrating technology into the curriculum. The primary benefits of technology integration include efficiency in accessing information, distribution and presentation of course materials, 

applications to calculate and record, flexibility to adapt to individual learning differences, and meeting real-world technological skill requirements. Even the simplest use of technology 

(e.g., spreadsheets, presentations, word processing, downloading information) appeals to faculty and learners.

Today, advanced communication technologies have enabled 

instant delivery of massive amounts of information in a variety 

of formats and user-defined levels. Some posit that the instantaneous availability of massive amounts of unstructured data 

leads to problem-solving errors (Sweller, 1988). Others take the 

opposing view, suggesting that “digital natives” have adapted 
16

their learning skills to accommodate the technology (Prensky, 

2001) and have acquired a self-regulating ability to organize the 

data necessary to resolve decision-making conflicts (Bandura 

1971, 1986). Further research is required on the subject, but 

advanced communication technologies are alluring to the educator because they provide the power to reach more students at 

a variety of learning levels (Jolley et al., 2004). Additionally, 

such technologies afford a multisensory approach to gaining 

and maintaining student cognitive and affective interest as long 

as such approaches are based on sound pedagogical principles 

(Achacoso, 2003). The quandary facing researchers and faculty 

members alike is the question of whether or not advanced communication technologies actually improve learning.

The literature on the subject is varied, but a majority of people 

writing on Ed Tech have found that technology alone does not 

necessarily enhance the learning process over traditional methods (Ehrmann, 1995; Sugrue, 2004). Rather, research has shown 

that technology can aid the learning process but only if applied 

correctly. Therefore, we can assert that although learning is not 

technology dependent, technology as an enabling tool has 

potential to improve the level of learning when properly applied.

One advantage of integrating technology into ID is its ability 

to present or provide access efficiently and effectively to a variety of information. However, it is imperative that educators 

shift the paradigm from where students learn from technology 

to where students use technology as a cognitive tool or learning 

enabler. The real power of Ed Tech comes not from automating 

information transmission but from enabling student education 

while engaging their desires to continue lifelong learning.

Cognitive tools allow students to interact with information to 

acquire, synthesize, create, and share new knowledge. Technology allows students to use cognitive tools to seek and present 

information while organizing and integrating knowledge (Robertson et al., 2007). Technology facilitates this process by enabling 

the learner to access and retrieve information beyond the limits 

of memory, which enables the student to return to previous 

information, engaging it throughout the learning process 

(Robertson et al., 2007).

Cognitive tools are distinct in their implications of technology. 

Jonassen and Carr (2000) distinguish the impact of learning 
17

from technology and that of learning with technology. Simply 

stated, when students work with technology, instead of being 

controlled by it, they enhance the technology’s capabilities, and 

the technology enhances their thinking and learning. This interaction empowers learners to become active and responsible 

filters of information who engage in directing their mental processes. Cognitive tools should allow students to “activate metacognitive learning strategies” (Jonassen & Carr, 2000). Metacognitive learning strategies are used when students encounter 

new information, connect it to their prior knowledge, and then 

construct and revise their schemata (Flavell, 1979). The effective 

use of cognitive tools should enable learners to undertake this 

process and assist them in experiencing cognitive processes that 

would be impossible without such tools (Mayes, 1992).

Technology to Promote Affective Learning

Research has proven that learners who are not engaged and 

motivated are not learning as effectively as their peers who are 

engaged and motivated. According to Rose and Meyer (2002), 

educators engage and motivate by providing a choice of content 

(print, audio, information, video, simulation, and instruction), 

adjustable levels of challenge, and choice of learning context 

since learners are unique, like fingerprints. Technology enables 

designers to embed video, pictures, sounds, and story lines while 

providing links to additional information and social networks 

that learners can access. In multimedia learning, the student 

engages in three cognitive processes: selecting, organizing, and 

integrating based on dual coding theory (Mayer, 1996). Additionally, the affective domain is engaged through an emotional story, 

an evocative image, a video, or mood-provoking music.

By properly designing and integrating with correct technology, 

the educator can emphasize the desired effect to engage the 

learner to promote knowledge construction and problem solving 

(Um, Song, & Plass, 2007). For example, consider an online 

instruction consisting of text explaining that one should avoid 

filling a gas can in the bed of a truck. Now consider the same 

learning goal using video showing an individual at the gas 

station as gas fumes—ignited by static electricity—explode, and 

flames engulf the truck. Such poignant examples, delivered by 
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means of technology, are designed to engage emotions while 

making people think about potential consequences.

Another proven influence on affect is socialization and personal interaction with others, including students and faculty. 

Social interaction can lead learners to make strong internalizations and can affect their reasoning and beliefs. Learners’ comprehension or retention of knowledge (cognitive learning) as well 

as their feelings about, attitudes toward, behavior during, and 

satisfaction with the course (affective learning) may also be 

influenced. Social presence has emerged as an important social 

factor in the field of education. To understand the concept of 

social presence, one must understand what socialization and 

presence entail (Guanwardena & Zittle, 1997). According to Kandwar and Swenson (2000), socialization refers to the “process by 

which people learn the characteristics of their group and the attitudes, values, and actions thought appropriate for them.” Presence—important in social learning to reach learning goals—is 

reported to have positive effects on student perceptions of the 

course’s communications and relevance (Jacobson, 2001).

The recent advance of several new Ed Techs such as online 

learning environments, social networking, mobile devices, and 

intelligent agents is reshaping the nature of Ed Tech. These 

technologies allow asynchronous and synchronous communication that facilitates socialization and social presence. Technology can facilitate communication across barriers of time 

and distance while enabling virtual communities with affective 

and social support that fosters deeper shifts in education practices (Dede, 1999). Educators are using these advances to meet 

affective learning objectives. The following Ed Techs focus on 

current and ongoing capabilities, thus facilitating the affective 

educational processes.

Online Learning Environments

Online learning environments encompass a variety of types 

and styles, providing different capabilities such as content management, discussion, assessments, and messaging. If properly 

designed and employed, these environments can facilitate affective and social interactions. The key is providing social, learning, and technology support in the learning environment (Chen, 

2007). All three areas impact affective learner characteristics. 
19

Successful learning environments must facilitate a variety of 

learners and educators across the spectrum of affective and 

cognitive knowledge levels. Successfully providing such support 

requires instructional designers to consider the ID process for 

the learner and to plan for costs, logistics, and faculty support 

in all three areas.

Social Networks

Social networks and social learning are coming of age as technology grows and the Internet expands across the world. Social 

learning can take place in discussion forums, chats, blogs, 

wikis, and virtual worlds. Social theory provides insight into 

why social networks need to be part of the learning process. 

According to social-learning theory, human behavior is based 

on continuous reciprocal interaction among individuals in terms 

of cognitive, behavioral, and environmental influences (Bandura, 

1971; Jones & Issroff, 2005). Preece (2000) emphasizes that, if 

online communities wish to be successful, developers and 

designers need to pay attention to social as well as technical 

issues while infusing sociability in communities that depend on 

trust, collaboration, and appropriate styles of communication.

Online-learning communities normally congregate around 

formally organized learning activities. Wenger’s concept of communities of practice (CoP) (1998) has gained acceptance across 

the education domain, enabled by new technologies that permit 

the development of virtual CoPs. Air University’s Commander’s 

Connection is one of those communities that has proven successful in allowing new and current squadron commanders to 

get together virtually and educate, assist, and update each 

other. CoPs have provided motivation and emotional support 

while allowing peers to operate in real-world contexts (Jones & 

Issroff, 2005).

Technology not only has the capability to engage students by 

enriching the learning environment, but also can assist the 

faculty. Professional networking can link educators as a community of peers to help establish best practices and pedagogical strategies. Such online communities also assist faculty 

engaging in research and provide a means for them to compare 

cognitive and affective strategies. Distance-learning technology 

also enables teachers to reach more students than face-to-face 
20

meetings would allow. An experienced teacher in the role of 

subject-matter expert may participate in the design, development, and implementation of both an online class and pedagogical techniques focused on cognitive or affective strategies 

that can aid novice educators; such a teacher could also act as 

a mentor (Wepner & Tao, 2002).

The most common method for social interaction in CoPs 

and other online venues is the discussion forum. The creation of a discussion forum to encourage social interaction 

among individuals while they undertake online studies has 

become a common practice as increasingly sophisticated 

learning-management systems pervade education. Pilkington and Walker (2003) assert that effective teaching and 

learning is predicated on the forum’s capacity to facilitate 

collaborative and critical discussion to “develop student 

ability to reason” for both cognitive and affective learning. 

As Roberts (2007) suggested, it is not just about participating but about how this participation can enrich studentlearning experiences.

CoPs, discussion forums, or online chats are all ways to integrate social learning and networking with the educational 

process. Learners are able to extend their range of learning opportunities by collaborating with others to achieve goals and 

complete assignments not otherwise possible. According to 

Woods and Ebersole (2003), a properly designed social-learning 

network facilitates interconnectedness and shared responsibility for learning outcomes, allowing cognitive and affective aspects of online learning to produce optimal results. Technology 

has facilitated social learning and brought it to a higher level of 

educational awareness. Further research is necessary to determine the best means to exploit it for optimized learning.

Virtual Worlds

Perhaps we are reaching the next stage of social presence 

through the use of virtual worlds, which are gaining acceptance as a viable teaching and learning tool. Virtual worlds 

can provide an immersive environment that facilitates a 

strong social presence. They allow simulated experiences 

not possible in school settings, increase learner engagement 
21

by visually immersing students, support new forms of interaction and collaboration with the potential to increase students’ knowledge and skills, and build self-efficacy (Metcalf, 

Clarke, & Dede, 2009).

Virtual experiences can have a more profound influence on 

affective outcomes than other pedagogy because multiple senses 

(visual, auditory, and tactile) are involved. Additionally, learning 

in virtual environments can be tailored to individual needs. 

Rather than learning by listening to lectures or reading, students will be able to access information, work collaboratively, 

and evaluate knowledge using virtual simulations. Although virtual worlds in education and training are still in their infancy, 

they show potential.

Massachusetts Institute of Technology Affective 

Computing: Human/Computer Interface

As discussed earlier, it is problematic to assess short-term 

affective status, and it is even more difficult to measure longterm affective learning outcomes. However, advanced technology 

is promising new means to provide affective feedback. The Massachusetts Institute of Technology (MIT) is actively researching 

ways to measure the affective state of learners via technology. 

One aspect of MIT’s research is the affect-sensitive AutoTutor, 

which aspires to keep students engaged, boost self-confidence, 

and maximize learning by narrowing the communicative gap 

between the highly emotional human and the emotionally challenged computer (D’Mello et al., 2008). AutoTutor is intended to 

be responsive to learners’ affective and cognitive states. Whether 

or not the affect-sensitive AutoTutor positively influences 

learning and engagement awaits further development and 

empirical testing (D’Mello et al., 2008). AutoTutor represents 

just one of a handful of related efforts currently being researched. Technology that senses or measures human affect 

will need to be considered as we design our future educational 

and training courses.

Affective-Reasoning Agents

Affective-reasoning agents are similar to an expert tutor who 

uses artificial intelligence to respond to a learner’s cognitive 
22

needs. These agents parse learner responses for affective content and respond realistically with correct emotional expressions to the human user. Similar to affective computing, they 

have the potential not only to provide social-learning contexts 

intertwined with affective reasoning, but also to provide a way 

to reach learners with inspiring, affective presentations and 

realistic experiences. If properly designed and executed, affectivereasoning agents can also offer powerful affective feedback, 

which can take the form of natural conversation, gestures, or 

verbal clues, allowing the learner better insight into and connectivity to the educational outcome the designer intended 

(McQuiggan & Lester, 2007). Like the work at MIT, affective 

reasoning is in its infancy, and more research is needed to find 

the proper mix of technology and design.

Mobile Learning

Technology also enriches learning by extending education 

and training away from normal education sites. Learners can 

take learning on the road, using laptops, mobile-learning devices (m-learning), and wireless or wired networks. Learners 

can then tie into Web sites, social networks, or e-learning sites 

(e.g., Blackboard), where they can engage in research, communicate with students or faculty, write papers, do homework, 

take tests, read required articles, or even catch the lecture they 

might have missed. Mobility allows formal and lifelong learners 

to control the learning experience in a number of dimensions 

(Paulsen, 1993).

Mobile technology allows learners to tailor education to their 

lifestyles. Learners can stay connected with other students, 

faculty, and instructional resources. The result is that learners 

feel more comfortable with the educational process and are 

more likely to internalize what they are studying and sharing 

(Prensky, 2001). Further, some learners are tied to their friends 

and business activities through their mobile devices, and the 

trend of using the devices may be culturally ingrained. The combination of convenience and connectivity can increase the level 

of social presence, which can improve the level of affect toward 

learning. The use of mobile devices requires active interest and 

precludes the passive process found in some traditional learning 
23

environments (Shen, Wang, & Shen, 2009). Businesses are starting to look at ways to take advantage of mobile and m-learning 

capability, including learning-content systems, assignment 

reminders, and learning aids. According to the eLearning Guild, 

over 30 percent of organizations surveyed currently deliver some 

amount of learning content through mobile platforms (e.g., iPod, 

Blackberry, or other smartphones).

Leadership

The affective domain is vital to overall learning, but it holds 

special interest to leaders and those individuals who develop 

tomorrow’s leaders. Leadership requires influencing people’s 

attitudes, motivations, and goals, which correlates directly with 

the factors comprising the affective domain. All leaders must 

be able to address problems and make decisions, but truly 

effective leaders must be able to create positive affect in themselves and their followers to motivate everyone toward a common 

goal. This synergy between leadership and affect makes affective learning a vital concern to the Air Force. The most likely 

means to develop motivated leaders who can motivate others is 

to cultivate them through substantive affective learning in Air 

Force education and training programs.

One approach to acquiring leadership skills involves studying 

the philosophy, habits, and methods of one or more highly successful leaders and then trying to develop a personal leadership 

style based on a single leader or a composite of several (Lorenz, 

2005). This method relies on inspiration to create affect in the 

learners toward leadership. A well-designed leadership course 

should provide a wide variety of leadership examples and highlight 

key achievements and methodologies that reinforce desired philosophy and traits. Ed Tech’s integration of video, audio, or other 

multimedia to grab learners’ attention by introducing relevant, informative, and inspirational leader aspects provides essential 

learner ownership (Keller, 1999a). Additionally, designers need 

to provide learners with opportunities to conduct discussions, 

engage in authentic practice, and build confidence as they apply 

and synthesize the desired philosophy and traits.

Recently, practitioners of leadership and business development have become increasingly interested in the formation of 
24

leadership networks as a way to strengthen relationships 

among leaders. Within groups, peer members build relationships with each other, based on cooperation rather than a chain 

of command (Wenger, 1998). Group members converse about 

their experiences as part of a shared social/cultural community, or perhaps just as people who share similar values (Preece, 2000). Learners participate in exercises virtually, online in 

games, or through authentic role-playing opportunities to build 

the confidence vital to leaders. Designers can use the advantage of technology to allow the learner to replay scenarios, discuss issues with peers, or try out a different leadership philosophy. These activities can occur whether learners are 

collocated or geographically separated. A related process entails developing future leaders through mentoring, which also 

relies on social relationships but involves interactions not only 

among peers, but also among senior leaders and younger protégés. The desired end state still requires the creation of positive affect in future leaders and their followers to motivate everyone toward a common goal.

Recommendations

The results of this study give rise to several recommendations that could help Air Force education and training develop 

knowledge-enabled Airmen and foster leadership. The first suggestion is to institutionalize affective learning throughout all 

aspects of Air Force education and training:

• Integrate affective objectives into the ID process.

• Develop and adopt a combined ID methodology that merges 

cognitive and affective concerns.

• Develop Air Force faculty who are sensitive to the student’s 

affective states, and devise empirically validated methods 

to positively impact affect.

• Promote policies that encourage affective-learning tactics, 

techniques, and procedures throughout Air Force education and training programs.
25

• Implement experienced Ed Tech manning positions at 

higher headquarters along with a similar institution at 

Air University.

Significant integration of affective learning will be possible 

only with the buy-in of Air Force leadership. Senior leaders 

must recognize the importance of affective learning and work 

to institute policies that promote its use in all Air Force education and training programs.

A second suggestion is that the Air Force actively develop and 

apply social networking and other technologies described in this 

study to achieve affective-learning goals. This may be problematic due to current limitations imposed by network security. 

Discussion boards, CoPs, streaming videos, chats, blogs, and 

other applications enabling social interactions are encumbered 

with security policies on military networks. Consequently, educational networks may be necessary before social-networking 

technologies can be employed throughout the Air Force. However, it is important for the Air Force to cultivate lifelong learners 

by encouraging engagement and social interchange during the 

learning process. Social networking is being exploited in civilian 

education and promises to change the face of learning from 

directed information exchange to a more learner-centered 

approach.

A third recommendation is to conduct further studies on affective learning to address questions regarding its use in and 

impact on Air Force education and training:

• How can cognitive and affective-design methods be combined 

to create a more effective overall curriculum-development 

process?

• What assessment or survey methods provide the best measurement of a learner’s affective state and success in meeting learning objectives?

• How does the learner’s affect influence cognitive learning?

• Which methods and technologies are most effective in 

building positive attitudes, motivation, leadership, and 

confidence?
26

Conclusion

This study is intended to help Air Force leadership and educators better understand the importance of affective learning 

in the development of Airmen as lifelong learners. Affective 

learning concerns learners’ attitudes, motivations, beliefs, and 

emotions. Unfortunately, the affective domain has been a neglected area because its characteristics are neither directly observable nor easily measured. Consequently, most educational 

systems evaluate student performance against cognitive proficiency rather than against affective measures. However, it is 

important to realize that affect is critical to the overall learning 

process since cognitive learning depends on attitude, motivation, and other affective factors.

It is necessary to include a learner’s emotional/cognitive 

state in the ID process to assist the learner in understanding 

the efficiency and satisfaction of the learning process. ID that 

merges affective and cognitive objectives is even more critical 

as more instruction is conducted through distance learning 

without a facilitator present. An important Air Force goal should 

be to partner technology with the affective and cognitive domains to provide distance students with an experience similar 

to that of in-residence students.

Technology offers the opportunity to promote affective learning through multimedia, social networking, mobile learning, 

and more. Additional study is needed to assist short- and longterm affective gains using technology. Social networks and 

learning are having successes and failures; further research is 

needed to gain more understanding of affective and cognitive 

linkages in social-learning environments. It is imperative that 

technology support education and not the other way around.

There is a great deal of overlap and synergy between the concepts of affect and leadership. Successful leaders must be able 

to motivate themselves and those they lead toward a common 

goal. How we encourage today’s learners impacts how they develop into tomorrow’s leaders. To be successful, affective learning must be institutionalized into Air Force culture, including 

strong support from senior leaders.
27

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