Author: admin

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nhilliar@purdue.edu

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• Portfolio: https://paedagogus.org/nch
• LinkedIn: https://www.linkedin.com/in/nathanial-hilliard-a10914168/
• E-Learning Heroes: https://community.articulate.com/users/nathan_hilliard/679679

Resume

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Demo

Live demo

Introduction

Ever wondered how to connect to a database from inside Storyline? Need to run your course from a webserver instead of an LMS and don’t have access to a Learning Record Store to save data? Want to pull data from a large collection that can’t be included in your project? Just want to learn something new? If any of these sound like you, then you may be interested in this article.

Note: If the database in the demo stops working, it is probably because I forgot to renew it. This free site requires weekly renewal.

I’ve been toying with parts of this on and off over the last couple of years. When I saw this question come up recently, I thought it might be time to put it all together. This approach was drawn from several online resources, but the specifics on database connections came from this very informative video series.

What You Need

• Storyline 360
• An online web server with PHP available
• A MySQL database that is accessible from the web
• Some knowledge of JavaScript
• Passing familiarity with reading and editing a PHP script
• Basic understanding of MySQL queries (and how to get your data into a database)

Overview

The overall process is that you build a Storyline slide that includes a web object. This does not need to be visible, but it will point to a web site on your web server that includes an index.php or index.html file (more on that later). You will use some JavaScript to pass your data from Storyline to the web object. The index file on your web server will receive this data. It then determines what to do with the data you passed and sends requests to the database. The database responds to the request, returning new data. The web server then sends this data back through the web object, to Storyline. From there, you can do whatever you want with it.

In keeping with the original question, this example queries a database of users using a username that you type. It then returns biographical information and image data to Storyline, which displays it on the slide.

In Storyline

The required variables are:

• action – “fetch” for this example, can be made into whatever action you want
• username – the username you entered in the text entry
• bio, loc, name – receives data returned from the database (for display)
• imgTag_1 (and 2) – these are the images used to display the returned image data

Since we need to communicate through the web object, the JavaScript used in the trigger first checks to see if the iframe is ready on the slide (bottom of script). It won’t appear until ready, so we need to wait until it is. When it’s ready, it calls the postMessage function. This builds your message from the action and your data (username), specifies who is supposed to receive it (approvedTarget), and uses postMessage to send it to the iframe.

The function also creates an event handler to listen for return messages from the iframe. This is where any data returned from the database will get processed. This handler first checks to see if the received message came from where we expected (approvedOrigin). If so, then we use the data found in event.data.

For this example, the returned data is a delimited string holding the name, location, biography, image URL, and base-64 image data from the database. Each entry is separated by a double quote. How you assemble and return the data string is up to you (more later).

Here, we send the information back to Storyline variables and use the image data to swap the displayed images in our tagged slide pictures. If an empty string is returned, then nothing matched our request.

On the Web Server

On your web server, you need a basic webpage (index.php) and a folder with a couple of other files. The easiest way to create these files is to create a new folder somewhere on your PC. Inside this, create a file called “index.php”. You also need to secure your website against allowing people to browse your files. In this folder, create a file called “.htaccess”. Make sure the first letter is a period. Inside that file, enter the following one line of text, and then save this file:

Options -Indexes

Now create another folder called “includes”. Inside includes, create two files called “formhandler.inc.php” and “dbh.inc.php”.

When we are done editing these files, you can zip the index.php file  and the includes folder together to upload to your website folder on the web server. Then unzip them and you’re ready to go. Delete the zip file after unzipping.

index.php (or index.html)

This is your webpage. All you need are the basics:

<!DOCTYPE html>
<html>
<head>
	</head>
	<body>
		<script>
			//JavaScript goes here
		</script>
	</body>
</html>

You will include some JavaScript in this file that will receive the message you sent from Storyline. It will decide how to handle the data you included and then it will make a POST request to transfer that data to another file in the includes folder. That is where the database communication will occur. The POST request here is akin to filling out a web form and clicking a submit button. This page will also listen for return messages from the POST request, and then, in turn, return the data in these messages back to Storyline.

The index.php file contains the <script></script> section. This holds the JavaScript. This script has a few functions and a main routine. The main routine first creates an event handler to listen for messages sent from Storyline. It verifies the origin sent with the one specified here to make sure the message is one you want to process. If not, it is ignored. The passed message data is split apart (using comma delimiters). It looks for “fetch” or “put” actions in the first position (we only use fetch here). You can change these to whatever suits your needs (adjust formhandler.inc.php accordingly).

Fetch will send your specified username to the database and then return its response. Because we need to wait for the response, we want to use an asynchronous function here. First, we create a request object (for sending the POST). I used XMLHttpRequest because I know how, but there are other possibly better ways. Then we set up an event handler to lister for this object to say it finished its task. If it succeeded, then we can call another function that will return the message with the database data to Storyline. Once the handler is set up, we make the POST request with the data bound for the database and then exit, waiting for a response.

formhandler.inc.php

The POST request goes to the PHP script on this page. Where JavaScript runs on your webpages in the browser (as you use it Storyline), PHP runs only on the server. It runs before the webpages go to the browser, so it is invisible. No one can see what goes on here.

This PHP script verifies that the call to this page was for a POST. If not, it is ignored. If POST, get the passed variable (username). Then establish a database connect by including another PHP script file (dbh.inc.php). Then, we create a MySQL query statement. The passed data is bound separately to the query (instead of including it in the query directly).  This separation prevents malicious data from hijacking your query. The statement is executed. We expect a single row to match, so we use fetch() to get it. We assemble the fetched data into a string delimited by a double quote character (use whatever is appropriate for your data). When ready, we use echo to output the text string, which is what gets returned to the POST request.

<?php  //Note: don’t use a closing tag in this script, leave it open
if ($_SERVER["REQUEST_METHOD"] == "POST") {
	// get data from mySql, and echo output to return the data to the requester
	$username = $_POST["username"];
	try {
		require_once "dbh.inc.php";//has DB connection information
		$query = "SELECT * FROM users WHERE username = :username;";	
		$stmt = $pdo->prepare($query);
		$stmt->bindParam(":username", $username);
		$stmt->execute();
		$row = $stmt->fetch();//get next line of data (all requested fields)
		$sep = '"';//specify data seperator for returned data
		//echo text to return the data to the POST requesting routine 
		echo $row["name"].$sep.$row["location"].$sep.$row["bio"].$sep.$row["url"].$sep.$row["image"];//get column contents
		//clear the database connecction
		$pdo = null;
		$stmt = null;
		die();//exit script
	} catch (PDOException $e) {
		die("Query failed: " . $e->getMessage());//if connection problem, exit script
	}
} else {
	die("Invalid Request");//if not a POST request, exit script
}

dbh.inc.php

This PHP script is included into the previous script. It contains the connection details for the database and creates the connection. Update the database host, database name, database username, and database password with your own information. Do not share it.

<?php  //Note: don’t use a closing tag in this script, leave it open

	$dsn = "mysql:host=hhhhhh;dbname=nnnnnnn";
	$dbusername = "uuuuuuuuu";
	$dbpassword = "ppppppppp";
	try {
		$pdo = new PDO($dsn, $dbusername, $dbpassword);
		$pdo->setAttribute(PDO::ATTR_ERRMODE, PDO::ERRMODE_EXCEPTION);
	} catch (PDOException $e) {
		echo "Connection failed: " . $e->getMessage();
	}

Final Thoughts

Requesting data from the database requires the asynchronous function so your script isn’t stuck waiting for a response. Just sending data to the database (the “put” section of the script in the index.php file) does not have to wait, so it uses a synchronous function.

To add additional functionality, you can create more action tags, pass them to index.php, and either make POST requests to additional formhandler script files, or update the existing fornhandler.inc.php file to accommodate more functions.

You can have your database on or separate from your web server. As long as you can communicate with it, this should work. I am unfamiliar with other types of databases, so I don’t know what specific changes might be required to connect to them.

The database structure is as shown below.

This was a a learning module for 3rd-grade students in 4-H that introduced the concept of digital agriculture and what its constituent components, digital and agriculture, mean in terms familiar to the learners.

• Responsibilities: Instructional Design, eLearning Development, Supplemental Content Development, Multimedia Design and Development using a combination of traditional and generative AI techniques
• Target Audience: 3rd grade 4-H students
• Tools Used: Articulate Storyline, Krita, Reallusion Cartoon Animator, Adobe Premiere, Generative AI
• Budget: Low
• Client: Purdue University Extension Services
• Year: 2024

Overview

As part of the larger and ongoing Digital Agriculture Project, Purdue Extension educators requested an online asynchronous learning module introducing digital agriculture to 3rd-grade learners involved in 4-H.

Agriculture continues to play a substantial and increasingly important role in human society around the globe. It is vital that upcoming students understand and develop an appreciation for agriculture and its role in solving problems of global interests. The goal is to enhance interest in agriculture in parallel with the sciences in upcoming students. This introductory module was meant to serve as a prequel to all of the subsequent digital agriculture topics targeting higher grade levels..

The overall Digital Agriculture project serves an audience spanning a wide range of grade levels. As one of the modules targeting elementary-level learners, this introductory module was designed to present content in a low text, high graphic format. With the goals of topic introduction and interest establishment, this approach lends itself to better engagement with younger learners.

The client agreed with my approach, feeling their learners for this topic would be better served by limiting the cognitive load associated with large amounts of otherwise novel content.

Project Origins

{Optional summary of how the project came to be and what influenced design decisions or tools}

Design Approach

{Optional summary of the justifications for the basis of the design. May include problems identified, theories used, project specific definitions, and sample integrated content – a few lines to several paragraphs}

Process

This project focused on relating agriculture to the everyday lives of younger learners, and introducing digital concepts in a way they may easily understand. A major hurdle was the extensive development of relevant graphical media to support the specialized topic matter. Once this was completed, the development of the final eLearning product was fairly straightforward.

Instructional Design

Working with the client, we identified the primary topics best suited for learner’s needs when getting started with digital agriculture in 4-H.

Each of these topics were fleshed-out through my own content research. Specific attention was given to agricultural applications related to youth interests and needs, and impacts they may have on their lives. Where possible, examples were placed into the agricultural context.

Text-Based Storyboard

I developed a detailed text-based storyboard, expanding on the topical outline, that followed the progression of the learner through various topic areas. This narrative outline established content scenes and described the presentation of individual sub-topics. This also served as the draft for module narration graphic design, and user interactions. I shared with with this this for content approval and feedback. Afterward, this expanded into a graphical storyboard.

Prototype

From the graphic storyboard and the draft narrative, media development began to produce topic-specific graphics, actors, and scenes. I completed initial scene design for select topics.

I also developed various interactive activities to improve learner engagement. These were submitted to the client for evaluation prior to full module completion.

The client provided approval on look and feel, as well as interactive scope.

Final Product

Final development of media content, narration scripts, and interactions followed client approval of prototypes. The detailed storyboards facilitated a streamlined development process.

Client Testimonial

{Optional paragraph summarizing client feedback or comments on final product}

Results and Takeaways

The final product is under evaluation with educators and target audience. Awaiting follow-up feedback and adjustment requests.

Since agriculture is a rapidly growing and increasingly important field, this module should provide a vital springboard to introduce younger learners to agricultural and technological topics, readying them to engage in advanced science and agriculturally-based disciplines.

I enjoyed creating this story-based module and I believe it will help engage younger learners more effectively than traditional text and video-based modules. A fine line exists between motivational and educational learning design. I strive to encompass both of these into my instructional design work.

Introduction

The role of theory in instructional design (ID) is that of foundational understanding. Theory underpins the rationale often hidden behind design decisions, and a lack of theoretical understanding may lead to misinterpretation of educational needs or misapplication of instructional techniques. The most educationally sound decisions require insight into why they are made and how they are meant to bring about a desired change.

Despite the utility of deeper understanding that theory may provide to the discipline of instructional design, understanding ID theory itself is not an easy task. In general, graduate students struggle with making sense of ID theory, especially as they define theory and differentiate among different types of theory (Belcher & Hirvela, 2007; Burri, 2017; Casanave & Li, 2015). Thus, an effective means to relate novel ID theory to learners is a necessary part of successful instruction. What follows outlines five characteristics theorized to provide a means of successfully engaging learners in improving their understanding of ID theory.

Theory

Application in teaching, as in many other areas, is often based on life experiences. People tend to teach the way they were taught, and the impacts of their teachers are reflected in how their instruction is designed. Despite this, individual experiences are limited and often one-sided, and there may be a lack of understanding as to how these otherwise familiar concepts of instruction came to be. Theory provides a glimpse behind the methods and application of instruction, revealing the fundamental aspects that fuel design decisions. To fully appreciate and absorb this, instructional design students must approach ID theory with a certain openness, awareness, and flexibility.

Objectivity

Foremost, and in possible opposition to prior experience, learners should approach theories with objectivity. Transformative learning theory describes the importance of reflecting upon current assumptions and how one’s view of the world may need to change (Kitchenham, 2008). Recognizing and quelling the preconceptions derived from one’s prior actions and experiences (Castillo-Montoya, 2017) may enhance the ability to reconcile new and potentially contradictory ideas. The familiarity of existing knowledge (Flannelly & Flannelly, 2000) and the inherent difficulty associated with understanding the often conflicting aspects of theory (Belcher & Hirvela, 2007; Burri, 2017) biases learners’ confidence toward what they already know. Driscoll (2004) describes how cognitive information processing and Gagné’s learning theories stress drawing on prior knowledge, and how meaningful learning theory values the relation of new information to old, but active reflection upon the potential flaws or shortcomings of one’s current knowledge and understanding supports the consideration of alternatives while suspending judgments that may limit objectivity (Flannelly & Flannelly, 2000). Learners should remain aware of what they know, but maintain an open mind.

Relevance

As with any difficult task, motivation can be key to successful perseverance in learning ID theory. Keller’s ARCS model (Driscoll, 2004) describes explicit consideration of the relevance of learning as a key element to achieving motivation in learners. Learners may feel personally satisfied about their efforts when the relevance of topics is clear (Cennamo & Braunlich, 1996). The ability to identify with any given ID theory will relate to one’s personal teaching philosophies and instructional preferences. The availability of personally relevant contextual references is also very important (Shen, 2013). Establishing a familiarity with ID theories may make them more relatable and facilitate comparisons and recognition of connections.

Inconsistencies

Through comparison and connection, learners may begin to recognize inconsistencies and contradictions between theories. Developmental learning theories (Driscoll, 2004) encourage teachers to help learners recognize the contradictions present in problems they face and their approaches to solving them. While such contradictions in ID theory are often the source of difficulty and frustration for learners (Casanave & Li, 2015; Reigeluth & Carr-Chellman, 2009), the ability to recognize such inconsistencies signifies the development of expert-like behavior (Baldwin, 2014). Novice learners tend to overlook contradictions, especially across disparate representations of ID theory, but as they gain experience they begin to question conflicts and formulate strategies to bring them to resolution (Baldwin, 2014). Recognition of these inconsistencies may result through productive friction (Hagel & Brown, 2005). Typically attributed as an effect of group work by individuals with differing experiences, productive friction may also extend to the differing works of individuals contributing to a unified cause, as is the case when considering multiple theories on instructional design. As a result the boundaries between individuals, or the boundaries between individual theories, expose different views of the world and highlight the difficulties of seamlessly meshing one view with another (Hagel & Brown, 2005).

Fuzziness

            Just as the boundaries between some ID theories may exhibit division and disconnects, which inhibit a smooth transition from application of one to another, approaches toward learning ID theories through isolated examination may create similar cognitive divides. Older students and adults tend to rely heavily on previous experience and use this to make more discrete categorizations when cognitively processing related subjects (Alexander & Enns, 1988; Hayes & Taplin, 1993). Developmental theorists such as Piaget and alternative theories such as the computational and framework approaches stress gradual cognitive development through processes of accommodation, assimilation, generalization, abstraction, reflection, and knowledge acquisition, especially in younger children (Driscoll, 2004). This aspect of learning, the ability to blur the lines between concepts and not presuppose the existence of rational divisions, has value when dealing with complex and disparate yet interconnected topics such as ID theory. Softening the boundaries between ID theories and considering the conditional truths supported by contextual application of different ID theories to real world ambiguities supports the fluidity of the learning process and the malleability of understanding required for cognitive growth (Zazkis, 1995).

Limits to Understanding

Consider the statement “The more I learn, the more I realize I do not understand”. As with many topics, learners may not realize the limits to their understanding while they are in the process of learning ID theory. Flannelly (2000) described learner overconfidence as highest on items of high difficulty and lowest on easy and familiar items. Increased familiarity with a topic accentuates the limits of one’s understanding. When dealing with novel and difficult topics such as ID theory, familiarity is low and learners may gravitate toward feelings of overconfidence in their knowledge, especially when bolstered through existing preconceptions. While Keller’s ARCS model (Driscoll, 2004) includes confidence as an important aspect of motivation, learners must not allow their developing knowledge to morph into an overconfidence of understanding. As ID theory abounds with inconsistency and ambiguity, attempts at rigid conceptualization in alignment with learners’ limited knowledge may result in much of the difficulty learners experience with theory (Belcher & Hirvela, 2007). Indeed, many of the preconceptions learners hold during the study of topics may persist after studies complete (Busom et al., 2017), continuing their influence . Objectivity may help alleviate some of this, but interpretations of the learning experience will be contingent upon the learners’ personal experiences, not just the intent of instructors or theory authors (Ricoeur, 1976; Scott-Baumann, 2011). Learners must realize that their ultimate understanding of ID theory will be a blend of their own and others’ views, and most importantly their understanding must make personal sense to be of use. Developmental computational and framework theories support gradual cognitive change, augmented by mental models and thought experiments (Driscoll, 2004). These internal representations provide learners the links with which to make connections to other ID theories and similar concepts. Personal representations such as these may not exactly replicate the original theorist’s intent, may not exactly match any of their peers, and may not perfectly represent any given ID theory. In combination with fuzzy boundaries, acceptance of inherent inconsistencies, and an objective outlook toward evolution however, these may result in highly relevant and learner accessible representations of ID theory.

Application

            Graduate students in learning design often have significant personal experience in education and instruction. This may be directly as an educator or, at a minimum, through many years as a learner. Either way, they may have experienced and/or implemented education across many topics and contexts. These experiences follow them into the classroom and are often a useful starting point from which to build new knowledge. This also holds for studies of ID theory, as personal experience may provide a much-needed framework from which to examine theories. The nature of ID theory, however, approaches the goal of education from multiple points of view, often resulting in ambiguity and confusion among theories through conflicting terminology, assumptions, and conceptualizations of instruction (Belcher & Hirvela, 2007; Reigeluth & Carr-Chellman, 2009). Over-reliance on learners’ existing preconceptions when undertaking ID theory may create discomfort and confusion. Learners should remain aware of their prior experiences, and draw from them accordingly, but must realize the limits of their current understanding when evaluating new theories that support what are perceived as otherwise familiar educational and instructional concepts (Flannelly & Flannelly, 2000).

ID theories are often presented in a sequential fashion, along some continuum allowing for transition between ideas. While attempts are made to draw connections between current and previously examined theories, the natural separations support encapsulation of individual theories by learners. This formation of cognitive boundaries, where specific theories are interpreted to have discrete characteristics and requirements (Alexander & Enns, 1988; Hayes & Taplin, 1993), complicates simultaneous integration across multiple ID theories. It can be helpful to encourage learners to consider the fluidity and dynamic nature of understanding during cognitive development (Driscoll, 2004) and the value of maintaining soft or fuzzy borders around differing theories so that internal concepts may more easily interconnect even if they only partially map to one another (Zazkis, 1995).

One learner outcome from the study of ID theory can be frustration due the abundance of ambiguity and the lack of definitive guidance on what truly comprises ID theory. As uncomfortable as this may be for learners, recognition of these issues signals the ongoing progression of learners from novice to expert (Baldwin, 2014). Realization of the limits of one’s understanding through the acquisition of knowledge and modification of cognitive frameworks (Driscoll, 2004) may also reduce the overconfidence exhibited when learners begin to process the difficult topics of ID theory through the lens of their own educational experience (Flannelly & Flannelly, 2000). Ideally, learners should be able to exchange feelings of frustration due to a lack clarity around ID theory for one of confidence contingent upon a need for ongoing learning and discovery.

Conclusion

The five characteristics of objectivity, relevance, inconsistencies, fuzziness, and limits to understanding comprise a theorized approach to effective learning of ID theory. Reflection on practices that support suspension of preconceptions, identification of personal relevance, realization of contradictions and ambiguity, maintenance of soft and fluid conceptual borders, and acceptance of the limits to understanding may support learners in the study of ID theory. The approach is somewhat contrary to normal education. Prior knowledge and previous experiences must be tempered to free the learner for consideration of new and potentially abstract concepts. Ideas and descriptions may be at odds between theories, with alternative views not necessarily in exclusionary competition. Clear categorizations are not really possible and attempts to create them may actually obscure the connections that interlink ID theories and make the instructional design process an amalgamation of ideas. Finally, after extensive study of ID theories is complete, learners may still experience discomfort with their lack of clarity and clear guidance in the use of ID theory. While demonstrably more knowledgeable, learners may personally feel that they still have more questions than answers.

Such is the nature of complex and interconnected topics like ID theory. Concepts are abstract, educational targets are in motion, subject populations are ever-dynamic, and a multitude of theories may attempt to achieve the same goal through application of very different worldviews. Learners must develop similar malleable, ill-defined characteristics in order to keep pace with the fluid nature of instructional design and the myriad of approaches available to solving educational problems. Anything less may leave learners shortsighted and ill-equipped to face the challenges ahead.

References

Alexander, T. M., & Enns, J. T. (1988). Age changes in the boundaries of fuzzy categories. Child Development, 1372-1386.

Baldwin, P. (2014). The Effectiveness of an academic literacy intervention to help university freshmen recognize and resolve inconsistencies across multiple texts (Publication Number 3633499) San Francisco, CA. https://search.proquest.com/docview/1611915224?accountid=13360

Belcher, D. D., & Hirvela, A. (2007). Do I need a theoretical framework? Doctoral students’ perspectives on the role of theory in dissertation research and writing. In T. Silva & P. K. Matsuda (Eds.), Practicing theory in second language writing (pp. 263-289). Parlor Press.

Burri, M. (2017). Making sense of theory: A doctoral student’s narrative of conceptualizing a theoretical framework. BC TEAL Journal, 2(1), 25-35.

Busom, I., Lopez-Mayan, C., & Panadés, J. (2017). Students’ persistent preconceptions and learning economic principles. The Journal of Economic Education, 48(2), 74-92.

Casanave, C. P., & Li, Y. (2015). Novices’ struggles with conceptual and theoretical framing in writing dissertations and papers for publication. Publications, 3(2), 104-119.

Castillo-Montoya, M. (2017). Deepening understanding of prior knowledge: What diverse first-generation college students in the US can teach us. Teaching in Higher Education, 22(5), 587-603.

Cennamo, K., & Braunlich, E. (1996). The Effects of relevance on mental effort. National Convention of the Association for Educational Communications and Technology, Indianapolis, IN.

Driscoll, M. (2004). Psychology of Learning (3 ed.). Pearson.

Flannelly, L. T., & Flannelly, K. J. (2000). Reducing people’s judgment bias about their level of knowledge. The Psychological Record, 50(3), 587-600.

Hagel, J., III, & Brown, J. S. (2005). The only sustainable edge: Why business strategy depends on productive friction and dynamic specialization. Harvard Business Press.

Hayes, B. K., & Taplin, J. E. (1993). Developmental differences in the use of prototype and exemplar-specific information. Journal of Experimental Child Psychology, 55(3), 329-352.

Kitchenham, A. (2008). The evolution of John Mezirow’s transformative learning theory. Journal of transformative education, 6(2), 104-123.

Reigeluth, C. M., & Carr-Chellman, A. A. (2009). Instructional-design theories and models. Volume III, Building a common knowledge base. London.

Ricoeur, P. (1976). Interpretation theory: Discourse and the surplus of meaning. TCU Press. https://doi.org/10.2307/468410

Scott-Baumann, A. (2011). Text as action, action as text? Ricoeur, λoƔoσ and the affirmative search for meaning in the ‘universe of discourse’. Discourse Studies, 13(5), 593-600. https://doi.org/10.1177/1461445611412760

Shen, L. (2013). Cognitive context’s role in discourse interpretation. Theory and Practice in Language Studies, 3(1), 88-93. https://doi.org/10.4304/tpls.3.1.88-93

Zazkis, R. (1995). Fuzzy thinking in non-fuzzy situations: Understanding students’ perspective. For the learning of mathematics, 15(3), 39-41.

Abstract

Increased reliance on the products of STEM fields creates a growing need for STEM professionals and students interested in STEM careers. Research focuses on ways to improve student interest and pursuit of STEM careers. Recent work also examines how student decisions to pursue STEM are made and influenced. Selection of STEM as a college major relies on both internal and external influences, many beyond student control. The decision-making process requires negations between the often-conflicting beliefs and needs of students and society. Students’ lived experiences impact how such information is interpreted and acted upon. Engagement experiences to foster student interest in STEM may relay realities incongruent with their inherent interests and impact long-term career decisions. Decisions are achieved by balancing values with knowledge, but the values and knowledge students’ use are largely derived through their discourses with others. Others may impact student decisions to overcome established obstacles to STEM, but they may also bear less student-centric objectives. Decisions of higher education path are not without consequence, and ill-made decisions may incur costs. Students may not recognize the influences at play but should be wary of efforts made to impact decisions to major in STEM fields.

Introduction

Many common conveniences such as mobile phones, GPS navigation, DNA screening, and increasingly effective medical treatments are possible courtesy of growth and innovation within the science, technology, engineering, and math (STEM) fields. Despite the importance of these fields, and supporting their growth through supplying qualified college graduates of STEM programs, a National Science Board (2004) report suggests decreasing enrollments in higher education STEM majors, and other works indicate that the United States is not generating sufficient STEM graduates to meet its needs (Atkin et al., 2002; Herrera & Hurtado, 2011). This diminishing flow of students into and through STEM programs is often referred to as a narrowing STEM pipeline, which begins early in education and progressively leaks potential STEM candidates as they progress to and through college, resulting in far fewer STEM graduates that those who may have expressed some interest in pursuing STEM along the way (Cannady et al., 2014). To counteract this decline, the General Accounting Office (2005) put out a call for active recruitment of students into STEM programs to fulfill the nation’s need. Encouraging secondary-school graduates to select a higher education STEM major is considered an important step in achieving a career in STEM (Atkin et al., 2002; Fouad, 2007; Herrera & Hurtado, 2011).

More than half of all students entering STEM majors in higher education ultimately select non-STEM majors or exit education entirely (Lomax, 2015). This effect may be even more pronounced for women and minorities (President’s Council of Advisors on Science and Technology, 2012). STEM students in the first year of higher education strongly exhibit these tendencies to switch to non-STEM majors (Piper & Krehbiel, 2015). Students switching out of STEM (and some who persist) commonly cited a loss of interest and motivation to pursue STEM as a primary factor (Hunter, 2019). At least half of students switching out of STEM felt under-informed about their selected STEM major (Thiry & Weston, 2019). Identification of an aptitude in an alternative non-STEM field was cited as the strongest motivator for switching (Hunter, 2019).

Much of the existing research on STEM education focuses on students’ STEM career guidance, stimulation of pre-college STEM interests, and persistence in higher education STEM programs (Atkin et al., 2002; Fouad, 2007; Herrera & Hurtado, 2011). Little work examines how high school graduates make their STEM choices for high education (Moakler & Kim, 2014). Some factors important to making STEM major choices include parental occupation, aptitude exam scores, and academic confidence (Moakler & Kim, 2014). In particular, students who select biological science majors also exhibited more flexibility in their choice of major (Sax et al., 2018). Female students are often found less likely to pursue STEM majors in higher education often due to developing diminished outcome expectations, suggesting that active efforts to increase STEM recruitment are warranted, particularly among women (Moakler & Kim, 2014). Contrarily, the field of biology exhibits a female majority amongst its students while maintaining its rigorous reputation, further encouraging highly qualified male applicants as well (Sax et al., 2018).

With biology as a potential model for other STEM fields to improve enrollment (especially of women) without loss of rigor (Sax et al., 2018), the use of advanced preparation STEM curriculum in pre-college education as a means to promote engagement and persistence in higher education STEM programs may yield more long term results than reliance on college STEM outreach and engagement programs (Lomax, 2015).  Outreach programs, while effectively improving student interest in and access to college STEM majors, may fail to result in the completion of STEM degrees by students selecting STEM majors or pursuit of STEM careers by STEM graduates (Lomax, 2015). The remainder of this review examines the concept of students choosing higher education STEM majors through formation of STEM identities, and how the elements of discourse, experience, and context inherent within STEM outreach or engagement programs may influence students’ STEM identity formation, yielding potentially impersistent increases in STEM enrollment in higher education.

STEM Choice

Much of the existing research on recruiting students to STEM examines student characteristics linked to potential success in STEM (Bøe, 2012; Rowan & Lynch, 2011; Stiles-Clarke & MacLeod, 2017; Wang, 2013) and means of encouraging students to pursue and remain engaged with STEM programs (Atkin et al., 2002; Fouad, 2007; Herrera & Hurtado, 2011). Recent works focus less on what actions may improve STEM engagement in favor of examining how and why students form relationships with STEM as a potential career field. For example, Godec (2018) exposed various strategies that enhanced girls perceived science identities. Similarly, Pechtelidis (2015) illustrated incongruities between how personal identities are interpreted inside and outside of STEM fields, which may affect a student’s feeling of acceptance within STEM.  Vincent-Ruz and Schunn (2019) described the interactions between STEM and non-STEM identities, suggesting that students’ STEM identities are malleable, subject to modification through experience, and may decline when in competition with those outside of STEM.

Wang (2013) suggests a key contributor to choosing a STEM major in higher education is the development of the intent to pursue STEM during the preceding years. Despite the student-centered aspect in forming this intent, it may be subject to external influences such as family expectations, cultural norms, and economic limitations, significantly impacting how students for STEM identities (Holmegaard, 2015). Godec (2018) added that while students may individually overcome or choose to ignore specific stereotypes and external expectations, their decisions are still subject to social acceptance which may further limit the realization of students’ personal STEM identities. When faced with a such conflicts, students often considered conforming their developing identities to social expectations more often than receiving social acceptance (Rowan & Lynch, 2011). Overall, choosing a STEM major for higher education is far from solely under student control (Holmegaard, 2015).

A Post-Structural Lens

Post-structuralism aids in the exploration of student generated narratives and shared discourses about the individual processes of identity formation. Researchers may gain additional insight into how choices of higher education major are realized through examination the individual truths of each student (Landry & MacLean, 1996). Since choice is derived through multiple, often conflicting influences, its realization requires “embrac[ing] the wisdom of a multiplicity of positions acknowledging the contradictions implicit in them and accommodating ambiguity” (Hutchinson & Wilson, 1994, p. 302).

Rowan and Lynch (2011) illustrate how individuals have difficulty reflecting accurately upon their own experiences and decisions. Limitations in memory, knowledge, understanding, interpretations, and communication all complicate evaluation of lived experiences and how they may contribute to a future self (Wamsted, 2012). Attempts by others to examine the experiences of individuals are similarly frustrated (Wamsted, 2018). External evaluation of students’ lived experiences is limited to an evaluation of their ongoing narratives and discourses. The abundance of ambiguity, multiple viewpoints, and variable contexts (Popoviciu et al., 2006) that complicate others’ interpretations also suggests how susceptible students may be to such influences.

As students struggle to find a place in their academic future where they can identify with their field, achieve a sense of belonging, and gain social acceptance they must examine their life experiences thus far, both as they see them and as seen by others. In doing, they engage in various forms of discourse to negotiate these alternate views and question the validity of their associated meanings in an attempt to discover the true nature of themselves (Mann, 1994; Slembrouck, 2004). Foucault (1972), defines discourse as a differentiated set of statements delivered through language. It essentially provides a mechanism to transfer consolidated packets of meaning, comprised of discursive statements. Discourse is commonly considered as an oral act, but Foucault’s work focused on written statements, and in reality any oral, written, or symbolic/iconic depiction may qualify as discursive statements (Blair, 1987). Within a discourse, discursive statements are organized to represent various concepts and ideas (Pentzold & Seidenglanz, 2006). Knowledge (and its associated power) becomes attached to statements as they interrelate and build upon other statements (Blair, 1987). Discourse then is a complex interworking and exchange of concepts and ideas between individuals, institutions, and environments, each impacting the other to some degree. The collective meaning derived from these discourses is socially constructed between each party and heavily influenced through the context in which it was delivered (Olsson, 2007).

Potential Costs

When considering the choices students make to select STEM related majors in higher education, a post-structural approach, which examines the intra and interpersonal discourses of students, affords researchers a glimpse into how such decisions are simultaneously individual and socially negotiated resolutions of potentially ambiguous and conflicting ideas. These same affordances also suggest means by which student choices may be influenced to enhance selection of STEM majors. In many of the studies described earlier (e.g., Bøe, 2012; Godec, 2018; Pechtelidis et al., 2015; Rowan & Lynch, 2011) there were legitimate obstacles inhibiting students’ individual freedom of choice regarding STEM pursuit in higher education. Efforts to improve STEM engagement, interest, and identity to overcome obstacles and increase students’ equity of choice may constitute an appropriate use of such influence. Problems may arise however if this influence extends beyond the compensatory and acts to dissuade students from legitimate alternatives to STEM.

As (Holmegaard, 2015) described, students may exhibit varying degrees of interest in STEM subjects, but this interest does not necessarily correlate with an interest to pursue STEM as a career. If students who are encouraged to choose STEM as a higher education path later realize that this conflicts with their long-term career interests, they must consider the future of their academic path. Continuing into an uncertain career choice may or may not work to students’ favor (e.g., see Hunter, 2019; Lomax, 2015; Piper & Krehbiel, 2015; Thiry & Weston, 2019), however changing out of STEM into another field (or exiting college entirely) comes with costs. For example, Foraker (2012) examines the effects of changing majors, especially after the introductory years of college, and highlights the potential negative impacts on student grades and graduation rates as well as the likelihood of prolonged enrollment prior to graduation. Sullivan (2010) further discusses the financial impacts on students associated with extending undergraduate enrollment.

The following discusses how discourse, experience, and context, issues key to clear interpretation of meaning (Olsson, 2007) come to affect how student choices are made and how students may experience external influence toward the formation of STEM identities that impact there choice of STEM majors in higher education.

Discourse and Language

Discourse is the primary means by which students may negotiate the meaning and value of differing ideas between themselves and others (Mann, 1994; Slembrouck, 2004). The collections of and relationships between discursive statements (i.e., various ideas or meanings) comprise the limits or scope of discourses (Hall, 2001). Language facilitates the assembly of statements (Graham, 2005) and is vital to the conceptualization and intra/intercommunication of perceptions and experience (Trifonas, 2009). This transfer of information is not exact however. Bakhtin (1981) suggests all language and all speakers are infused with their own values, permeating even the most basic of statements, thus there is always something gained or lost in the process of transfer.

Experience Through Action as Text

Experience plays an important role in choice and student decisions toward STEM majors (e.g., see Bottia et al., 2015; Bøe, 2012; Vincent-Ruz & Schunn, 2019). Engagement in action often lies at the center of one’s experience. Indeed, the performance of actions actually precedes any significant transfer of information, to others or to oneself, about the experience itself (Scott-Baumann, 2011). In science discourses in particular, students’ everyday experiences serve to support their own ideas, catalyze change in their own and others’ ideas, and promote change in their and their peers’ conceptions of science (Na & Song, 2014)..

While everyday life provides an abundance of experience, actions may become meaningful when they come to represent something important in an individual’s life; that is when the significance of the action extends beyond its initial occurrence (Ricoeur, 1971). Such meaningful actions may be self-initiated or orchestrated by others, but either way the meaning must be interpreted from the experience. As with any sign or symbol meant to transfer ideas or information within a discourse, actions and experience may be considered as a form of text (Scott-Baumann, 2011), where text here implies the statements of a discourse that must be analyzed from the point of view of the reader (i.e., recipient of the action) (Foucault, 1972). Discursive statements through actions (action-events) bear similarity to acts of oral discourse (speech acts): Both are experienced by a target, both are ephemeral constructions, and both relay some form of meaning to the individual (Ricoeur, 1971). Thus, as with any written or spoken discursive statement, there may be disagreement between the motivation and intent of the authors of actions and the interpreted understanding of the recipients (Scott-Baumann, 2011). Ricoeur (1976) further suggests that direct transfer of an experience from author to recipient is not possible without an intervening alteration of the intended meaning, influenced by the lived-experiences and interpretations of the target. While experience through action may be planned as part of a discourse, possibly in conjunction with other types of statements, the message delivered is subject to reinterpretation through the available contexts of the recipient’s lived experiences.

Context

Since the context available to recipients is highly relevant to how they may interpret any particular discursive formation, authors of discourse may consider and make efforts to supplement the contexts made available through an individual’s lived experiences in an attempt to improve the fidelity of their intended message (Shen, 2013). A primary purpose of messaging through discourse is to exert influence, sway others in the world, and enact change (Clarke, 2015). Post-structuralism supports the concept that ideas represented through discourse need not be grounded in reality if they are supported by other powerful, well-formed discourses. Indeed, misrepresentations of reality may result as byproducts of other well-established, accepted discourses (e.g., an over-realization of behavioral problems in children stemming from an established discourse describing the ideal child) (Lanas & Brunila, 2019). Discourse constructs rather than represents reality (Pinar et al., 1995). Its goal is to evoke action more than to simply inform (Clarke, 2015).

To achieve the desired communicative goals, access to relevant context is a necessity. As Derrida (1944) stated, “there is nothing out-of-context” (p. 158); interpretations are individualized, built from one’s own experiences. There is no inherent meaning outside the context used for interpretation. Shen (2013) adds that since individuals exhibit such variety in their lives and their experiences, they may draw from any number contextual references when attempting to interpret discourse; to achieve the desired interpretation, an appropriate context must be available. This need not be the only available context and certainly, alternate contexts may yield very different interpretations. Shen relates this to the principle of relevance: When multiple contexts are available that would yield differing interpretations of a given discursive statement, the most likely result is the first to have sufficient contextual backing. Essentially, the recipient of discourse will expend the least effort possible to make adequate sense of what was just experienced.

This point is critical for those who desire to communicate a precise message through discourse. While an individual may have a multitude of experiential contexts from which to draw, contexts recently constructed through carefully coordinated discursive exchanges that adequately support the original intent are the most likely to support that interpretation. This application and manipulation of context to influence discourse interpretation parallels the use of language to organize and deliver discursive statements intended to convey specific meanings.

Effects on Student Choice

The process of choice, particularly with students selecting their academic fields and potential future careers, is complicated and interconnected without clear correct solutions. Paul (1986) suggests that choice is a messy problem, one that requires evaluation of a multitude of experiences and competing perspectives, all interpreted through the individual contexts available to the students (Reznitskaya & Sternberg, 2012). This contextual interpretation of experiences mirrors that required by discourse.

Choice of academic path for students involves not only personal negotiation of interests and identity but also integration of influences and expectations from external pressures, such as from social, cultural, or familial sources (Godec, 2018; Holmegaard, 2015). Students are left to balance their decisions amongst the internal and external influences, considering what values those may represent. Reznitskaya and Sternberg (2012) however question how such values are determined and who decides which values are more right than others, and thus should weigh more heavily in decisions.

Wise students, as suggested by Reznitskaya and Sternberg (2012), will primarily base decisions upon a union of their own knowledge and values along with a consideration of any external inputs or expectations over the short and long term. Student knowledge and values are, to a large degree, developed through the discourses encountered throughout their academic careers. As suggested by Clarke (2015) and Lanas and Brunila (2019), discourse may serve more to exert influence than convey factual information, constructing a perceived reality that does not necessarily exist outside of the discourse. Under these circumstances, the origin of the knowledge and values contributing to the decisions students make about their academic careers is at question.

Throughout primary and secondary education, ample opportunities exist to establish supportive and perpetuating discourses involving action as experience. If STEM outreach or engagement experiences include meaningful actions, such as those promoting a sense of identity, belonging, or purpose in students, those experiences may be interpreted by students as part of an ongoing discourse that was designed to convey a specific sense of their personal STEM reality. As students undoubtedly exhibit a diverse array of lived experiences, the contexts students use for interpretation may vary significantly. Thus, appropriate contexts for the discourse author’s desired intent could be embedded directly into the experiences or built up over time through student interactions with previous discourses.

A simple example may be extended from Godec (2018) who examines how girls who may or may not exhibit an interest in STEM must cope with both personal and social expectations when developing a gender related identity compatible with a career in a STEM field. Individual acceptance of a STEM identity is in itself inadequate as the identity must also meet the gender expectations of her existing social networks. Given an experiential engagement activity designed to promote interest and identification with STEM as a viable career path, success requires the female student to have a referenceable personal context allowing the desired interpretation of I feel as I can do, I can be successful at, and I can be accepted in a STEM career. If relevancy theory is considered (Shen, 2013), the context would need to be readily accessible and able to outcompete any preexisting contexts that may not support the desired interpretation. A direct approach to ensuring the appropriate context would be to embed the gender roles which would best fulfil the expectations of her particular social networks (e.g., focusing on race, culture, social, education, or other particulars as appropriate for the audience). In this way, an appropriate context sufficiently supporting the intent of the authors of the STEM experience is immediately apparent and accessible to the student, and available to outcompete alternative contexts which may already exist based on the student’s life experiences.

A process such as this may work to serve the original intent of the authors of the experience, which is to increase a female student’s ability to identify with STEM careers and increase her likelihood of pursuing STEM in higher education. In cases of compensating for legitimate obstacles to STEM pursuit due to conflicting personal and social expectations and acceptances, this process may be acceptable and serve a greater good for both the student and society. Alternatively, this may also work to offset legitimate disparity between a student’s interest in pursuing STEM and society’s need for students to pursue STEM. Holmegaard (2015) and Vincent-Ruz and Schunn (2019) describe how competing or alternative interests may either work together or compete against each other in regard to STEM interest. Holmegaard further shows how such interests competed equally with STEM in relation to the choice of a STEM or an alternative non-STEM major in higher education. Thus, while STEM identity may be enhanced through the perceived reality a discourse of active engagement creates, implementing STEM outreach or engagement programs to entice students into pursuing STEM in higher education may place the (biased) needs of society over the individual needs of the student. Such biases ultimately may not be visible to students, however. Realization of how language and discourse may represent differing motivations and how this may bias student decisions develops only over time and with exposure to multiple versions of similar experiences, authored with differing intentions (Case, 2005).

Conclusion

The increasing need for STEM graduates to meet the nation’s growing demand for STEM related careers is evident. Promotion of STEM as a viable career is both valuable and necessary to overcome persistent biases and inequities in academia and industry. Care is warranted, however. Concerted efforts to combat inadequate numbers of STEM graduates with purely increased throughput achieved by way of ubiquitous outreach and engagement programs may not be the best solution. Increased enrollment into STEM is an excellent goal for students truly interested, motivated, and contented with the career path STEM may offer. The use of discourse, action as experience, and context as a gentle manipulator to offset oppression, discrimination, and exclusion of students who would truly enjoy and thrive in STEM is a worthy goal. The use of discourse and context manipulation to ensure success of outreach and engagement programs through sweeping increases in STEM enrollment at the risk of actively inhibiting legitimate competing interests and student autonomy is not. When discourse intends to shape perceived reality, to exert power over others (Pinar et al., 1995), its motives must be questioned. When applying such discursive influence over students to fulfil external agendas, academic institutions flirt with misappropriation of their power, a potential warned of by Foucault (as cited in Besley, 2015). One should be particularly wary and critical when educational discourse is enacted to achieve particular goals in the name of serving a greater good (Besley, 2015).

Limitations

Existing research does not significantly address the subject of this review. Consequentially, a variety of references were drawn from the core topic areas and unified to illustrate the issue of student choice of STEM majors in higher education. Little of the available research is tightly focused on STEM as it treats its specific topics. Additionally, the intended goal of any given experiential activities (e.g., STEM engagement) may be unknown. They may strive to overcome obstacles and improve equity and access to students or, they may attempt to bolster STEM program enrollment to meet specific institutional goals. The described studies also provide limited insight into the impact such engagement makes on students, whether choosing to pursue STEM or another field. Finally, much this work draws on theoretical discussions around the interpretation of discourse with the addition of limited STEM related research. Further work focused on STEM is needed in support of the key points of engagement experience designs, student interpretation of engagement, and attrition due to alternative interests.

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Exploring a Theoretical Framework for How Students May Be (Inappropriately) Directed Into STEM.

Overview

The progression of students into and through K-16 STEM programs can be described through a form of directed constructivism. Students develop or construct knowledge and understanding through their experiences in the environment, and these experiences may be more or less self-directed depending upon the sociocultural influences of that environment.  Learning and development is tied to experiences in the social world and in particular, the influence of others more experienced than the learner can greatly affect the effectiveness and direction of learning (Vygotsky, 1978).  The decisions students make to pursue a path in STEM education may therefore be influenced by certain elements of their sociocultural environment and those elements are represented here by the following theories.  Cognitive evaluation theory describes the influence of external motivators for an activity and the corresponding decrease in internal motivation that may result from relying on outside forces to drive action (Deci & Ryan, 1985).  Social cognitive theory supports social learning and observing others for use as models of desired behavior.  Support, both social and physical, helps to bolster a sense of self-efficacy and produce an effective learning environment (Bandura, 2001).  Role theory supports both identification of one’s place in the greater sociocultural environment and the expectations that environment places on the individual.  The clarification of boundaries provides predetermined guidance for learners’ behavior and actions (Biddle, 1986).  Finally, expectancy theory relates anticipated outcomes with associated actions (Vroom, 1995).  Educational goals may be socially defined and linked to a particular benefit or utility, which then guides learners to pursue these goals in order to achieve the expected outcome.  This framework is is designed to support investigation of the research question: How does extrinsic motivation direct students into STEM careers for which they exhibit inadequate intrinsic interest?

Cognitive Evaluation Theory

Cognitive evaluation theory describes a behavioral response where the application of extrinsic rewards or motivators to a behavior subsequently reduces the intrinsic motivation available for the same or similar behaviors due to a perceived externalization of control (Deci & Ryan, 1985).  Essentially, the reason why one would perform a task has shifted from an internal desire to an external requirement, resulting in a loss of intrinsic motivation.  Self-motivated practice of skills is an important aspect of learning (Piaget, 1962, p. 150).  Social conscription of a student’s intrinsic interest in STEM and creation of an educational environment that perpetually recognizes and evaluates the status and development of this interest moves control of the student’s STEM related actions away from the student and into the sociocultural environment.  The learner’s interest in STEM likely remains and continues to develop, but the basis for the interest is no longer centered within the learner.

Three key aspects to cognitive evaluation are:  Shifting the identified drive for action away from the learner will dampen intrinsic motivation, external influences will affect a learner’s intrinsic motivation based upon the effect of the influences on perceived competence, and rewards will influence the externalization of drive, perceived competence, and intrinsic motivation according to the degree of control over or liberation of the learner they provide (Deci & Ryan, 1985).  To have impact, these effects must have salience and expectancy, or meaning to the learner and reasonable likelihood of occurrence (Deci & Ryan, 1985), but may otherwise vary in form taken (Frey, 2012).   In the case of STEM education, this may consist of increased attention, recognition, or rewards for exhibiting educational interest and efforts.  Later this may evolve into monetary compensation for internships and other related work experience within STEM.

Social Cognitive Theory

Interaction between students within STEM education promotes learning through social experience and observation, and is described as part of social cognitive theory (Bandura, 2001).  Learning is influenced by the interaction of the individual with the observable behaviors of others, the individual’s confidence in their ability to perform similar behaviors, their actual ability doing the behaviors, as well as support and encouragement from the physical and social environment.  The combination of an observer’s sense of self-efficacy or perceived ability to succeed in a behavior, receipt of encouraging responses for completion of behaviors, and the conductivity of the learning environment for success influences any subsequent efforts to reproduce the observed behaviors (Bandura, 2001).  In this sense, students use their peers as models of activity and behavior and progressively increase their knowledge, understanding, and engagement with STEM.  In addition to peer support, educators, parents, professionals, and other STEM role models provide the encouragement, verbal persuasion, and additional mental or physical support needed to bolster student self-efficacy and increase outcome expectations.  This encourages development of the requisite skills and furthers student progression into more formalized STEM education pathways.

Role Theory

Biddle (1986) describes role theory as defining the accepted and desired characteristics of established roles in society.  Role theory suggests that much of a person’s activity serves primarily to fulfill their role, and that role may influence or define the behaviors a person elicits.  Role theory establishes what goals to pursue, what tasks are necessary, and what performance is required.  Key aspects of role theory include consensus, conformity, and role conflict.  Consensus informs socially agreed upon expectations for behavior where those in a role know how they are to act and those outside know what they can expect.  Conformity implies behavioral compliance, and may stem from either social imitation or deliberate emulation of role models and peers.  Finally, role conflict may arise when there is a public and personal disconnect in the expected behavior associated with one’s role, leading to disruptive stresses and pressure (Biddle, 1986).  Students therefore maintain proximity to their selected STEM pathway (i.e., role in STEM education) through a combination of behavioral role fulfillment (as defined by educators, career domains, etc.) and behavioral emulation of others in the same role.  In the case of role conflict, disparity between expected and enacted behaviors may cause a reassessment of the student’s role in STEM education.  This can push the student away from their established STEM pathway, back into the broader STEM education space where they may expand their STEM experience through resumed social interactions and potentially progress toward another formalized STEM pathway.  As education advances, STEM pathways become more specialized and technically demanding.  This inhibits changes into or out of a given STEM pathway by virtue of this student role becoming increasingly differentiated from alternative STEM and non-STEM roles.

Expectancy Theory

Students are expected to make forward progress along their increasingly demanding STEM pathway, fulfilling their role in STEM education.  Incentive for this progress emanates from the anticipated utility of a potential outcome, socioculturally defined here as a professional position in a STEM field.  This describes an aspect of Vroom’s (1995) expectancy theory, the premise of which is that while the choices a person makes may not always be the best choices, the person considers them the best for their purposes at the time they are made.  Essentially, even though the outcome cannot be known a priori, actions result from decisions that appear to support the most preferred outcome.  Preference here is given to the direction rather than the intensity of actions, leading students along their identified STEM pathway toward the anticipated goal.  It is noteworthy that the potential utility of a particular goal may be more closely related to where the goal may lead rather than satisfaction with the goal itself (Vroom, 1995, p. 18).  A professional position in STEM may therefore represent more of a means to an end than an end in itself.

There are three key aspects to expectancy theory: valence, instrumentality, and expectancy.  Valence is similar to incentive, attitude, and utility and indicates a preference in potential outcomes.  This is in contrast to need, motive, value, and interest which suggest an intensity of desire for potential outcomes.  There may be significant discrepancy between the expected and actual satisfaction of particular outcomes (Vroom, 1995).  Instrumentality represents a relationship between outcomes, or the potential that achieving one outcome will lead to another desired outcome.  It may also be considered in relation to the likelihood of success of such an outcome (Van Eerde & Thierry, 1996).  Expectancy is the belief that a given action will result in a particular outcome, and may also be interpreted as the likelihood of an effort yielding a result (Van Eerde & Thierry, 1996).  Expectancy thus represents a relation between actions and outcomes.  Together, the elements of valence, instrumentality, and expectancy define a goal and identify its potential utility to students following a STEM education pathway.  As long as students can identify a goal that offers potential satisfaction and appears achievable, they have an impetus for action toward forward progress along their STEM pathway.

Combination of Theories into a Framework

The theories described above help to frame and clarify the processes that impact student decisions to enter and persist in STEM education fields.  Where student engagement with STEM related activities may be initially casual and sustained through intrinsic forces, cognitive evaluation theory now isolates this engagement within an educational frame, subject to formal evaluation and judgement.  Motivation shifts its locus, transitioning from personal fulfillment toward external achievement, resulting in slow diminishment of self-determination (Deci & Ryan, 1985; Frey, 2012).  Within the social structure of education, social cognitive theory further draws students into STEM aligned roles.  Regular interaction and supportive environments foster the acquisition and transfer of knowledge through demonstrated behaviors.  Encouragement coupled with successful experiences builds self-efficacy (Bandura, 2001).  Combined, these encourage commitment to a path toward STEM education, framed by role theory.  Acceptance of this STEM aligned role both defines what others expect of the student and what the student expects of themselves, further dampening self-determination.  Similar to the behavioral influences of social cognitive theory, role theory describes behavioral compliance through social conformity (Biddle, 1986). Overall, this stabilizes the student’s role and maintains their position along the STEM pathway.  In as much as the goal of STEM education is to progress toward a professional position in STEM, progress must be made to that end.  Through expectancy theory, the driving force can be explained as the student’s expectation that successful completion of their educational path (i.e., their STEM education role) will be instrumental in obtaining their preferred outcome, a professional position in a STEM field (Vroom, 1995; Van Eerde & Thierry, 1996).  In combination with effects from the other theories such as shifting motivation from intrinsic toward extrinsic (cognitive evaluation theory), emulation and conformity of behavior (social cognitive and role theory), and increase of self-efficacy (social cognitive theory), this supports the actions that drive the progression and belief in the achievability of the end goal.

References

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Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum Press.

Frey, B. (2012). Crowding out and crowding in of intrinsic preferences. In E. Brousseau, T. Dedeurwaerdere, & B. Siebenhuner (Eds.), Reflexive governance for global public goods (pp. 75-83). Cambridge, MA: The MIT Press.

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