Peer Reviewed Elementary Teach Students How to Resolve Problems on Their Own

Introduction

As grade sizes in teaching are increasing and technology is impacting on education at all levels, these trends create pregnant challenges for teachers every bit they attempt to support individual students. Technology undoubtedly provides substantial advantages for students, enabling them to admission information from effectually the planet hands and at whatever fourth dimension. The advantages and disadvantages of the increased use of technology have come to light over time equally students increasingly engage with new innovations. In this review, we will accost an upshot that has become progressively evident in digital learning environments but is relevant to all educational settings, particularly as class sizes grow. We will explore the difficulties in attempting to sympathise and account for the struggles students experience while learning a item emphasis on what happens when students experience difficulties and become confused.

Running into problems while learning is often accompanied past an emotional response. Emotion, more broadly, plays a vital role in the integration of new knowledge with prior knowledge. This has been found to be the case in brain imaging studies (due east.thousand., LeDoux, 1992), laboratory-based studies (east.m., Isen et al., 1987), and applied educational studies (due east.g., Pekrun, 2005). A clear case of how emotion can impact on the learning process is where information technology creates an obstruction to learning, reflected in, for case, the vast torso of piece of work that has examined the detrimental effect of feet on the learning of mathematics (Hembree, 1990). Similarly, confusion has been associated with blockages or impasses in the learning procedure (Kennedy and Social club, 2016).

Despite its importance, understanding, identifying and responding to difficulties and the resulting emotions in learning tin be problematic, particularly in larger classes and in digital environments. Without the affordances of synchronous face-to-face human interaction in digital environments, emotions like defoliation are difficult to discover. It is therefore challenging to respond to students with support or feedback to help their progress when they are stuck and become dislocated. Humans are uniquely tuned to respond to the emotional reactions of other humans (Damasio, 1994). Intuitively we know what it is like to feel dislocated every bit a event of a difficulty in the learning process, nonetheless defoliation is non regarded equally one of the "basic" emotions: like, for instance, happiness, sadness, and anger (Ekman, 2008). And while student defoliation is relatively easy for an experienced teacher to notice in face-to-face settings (Lepper and Woolverton, 2002), it is a complex emotion that is difficult to explain scientifically (Silvia, 2010; Pekrun and Stephens, 2011). But nosotros know that confusion is both commonly felt by students, is able to exist diagnosed by teachers, and able to exist resolved productively with teacher support (encounter for instance, Lehman et al., 2008). Thus, at the most cardinal level, confusion is both widely experienced and relatively hands detected by teachers, despite the dubiety well-nigh the exact relationship betwixt difficulties and emotional responses in learning. Thus, student emotions, such as confusion, are relatively straightforward for experienced teachers to detect, sympathise and respond to in contiguous settings with relatively minor class sizes (come across Woolfolk and Brooks, 1983; Woolf et al., 2009; Mainhard et al., 2018). The same is not true in digital environments or large classes. Emotions are less obvious to teachers when at that place are many students or when they interact with students via electronic methods (Wosnitza and Volet, 2005). This ways that alternate practices are needed to respond to students when they experience difficulties in these emerging environments.

The increased difficulty in detecting and responding to student emotions is one of several key reasons why a deeper understanding of difficulties and associated emotional responses is needed as new technologies and increasing course sizes impact education. Digital learning environments, especially online or distance learning environments, are frequently explicitly designed and so that students will have flexibility and autonomy in their studies. Students, when studying online or at a distance, are ofttimes able to admission form material and resources in their own time (and place) and are often not constrained past centralized timetables. Equally a result, there is often a greater onus on students in these environments to be more autonomous and cocky-directed in their learning (Huang, 2002). Thus, increased learning flexibility often leads to students having fewer opportunities for engaging with teaching staff and receiving feedback in real fourth dimension (Mansour and Mupinga, 2007). While activities can be fabricated available in the class of webinars and other synchronous formats, there remains a substantial responsibility on students to exist democratic and brand good decisions about their ain progress without requiring the existent-time intervention of teaching staff.

Digital learning environments that largely provide self-directed students with autonomy and flexibility can potentially be created to detect and reply to student difficulties, but this potential has not still been realized (Arguel et al., 2017). A key claiming for educational applied science researchers and educators is to create digital environments that are better able to provide support for and potentially respond to difficulties and the resulting emotions such as confusion, without the requirement of having a teacher on-call to back up students. For this to occur, sophisticated digital learning environments need to be created that tin support students in their autonomous, personalized and cocky-directed learning and provide feedback that in some way, emulates what a teacher does in more traditional, face up-to-face up settings.

In order for a digital learning surround to exist responsive to difficulties—or indeed to other emotions that touch on on learning—it is necessary for the arrangement to find the emotions that students experience during their learning (Arguel et al., 2017). These emotional responses are the key indicator teachers use in contiguous settings to determine when students are having issues. Given the difficulty of identifying emotions in digital learning environments in ways that humans can in face-to-face environments, this is a particularly vexing issue and one that has led to the growth of the burgeoning field of affective calculating (Picard, 2000). A second requirement is that digital learning environments need to exist reactive to emotional responses such every bit confusion once these responses accept been detected. For case, it would exist useful if confused learners were given organisation-generated, programmed support to assistance them resolve their difficulties within the environment itself. Without a teacher present and without whatsoever automated back up, information technology is possible that a student may succumb to their confusion, become frustrated and, as a result, disengage entirely (D'Mello and Graesser, 2014). While it is difficult enough to determine when students get confused in these environments, it is even more than complex to know when and how to intervene to preclude the confusion from becoming boredom or frustration. Finally, it would be a distinct reward if any response or feedback that a digital learning surround provided a confused student could be tailored and personalized to the individual educatee and their learning pathway, progress and process (Social club, 2018). Teachers are able to apace suit to an private student's emotional responses in a classroom in smaller classes. This enables teachers to intervene with individualized, customized assistance and feedback for students, which can aid them manage both their emotions and their arroyo to the particular learning activity they are finding confusing. Effective intervention represents a significant challenge for designers of digital learning environments as teachers are skilful at responding to student emotions in nuanced and personalized means that are not easily programmed into a digital system.

Taken together, information technology is credible that the increased use of digital learning environments has created a need for improve agreement and intervening when students feel difficulties and become confused. This situation is, even so, not helped by ongoing theorize in the literature as to whether difficulties in the learning process resulting in confusion are detrimental or beneficial for learning (Arguel et al., 2017). For example, Dweck (1986) argues that confusion is consistently detrimental to learning and is mediated by prior achievement, IQ scores, and confidence. She suggests that students who take poor prior achievement and confidence are at risk of attributing the feel of reaching a learning impasse and their resulting emotional response to their lack of aptitude. That is, students who become dislocated while completing a learning activity may interpret their confusion as a sign that they are incapable of learning the material. This argument aligns with a body of literature showing that persistent defoliation can lead to frustration and colorlessness, which as a result has a negative bear on on learning (D'Mello and Graesser, 2014). More than recently, however, research has suggested that difficulties resulting in defoliation can benefit student learning. This is perhaps all-time exemplified in the research on what have been labeled "desirable difficulties" (Bjork and Bjork, 2011), specific features of the learning situation that introduce beneficial difficulties that reliably raise learning. Along similar lines, D'Mello et al. (2014) found that inducing difficulties and defoliation in an intelligent tutoring arrangement appeared to heighten learning. Moreover, some research has indicated that difficulties may be particularly beneficial for conceptual learning, where students sometimes need to overcome misconceptions before developing a more sophisticated understanding of the topic area (Kennedy and Lodge, 2016). For case, Chen et al. (2013) developed a predict-observe-explain activity nigh ordinarily misconceived notions in electronics. Conflicting information was presented to students in the grade of scenarios and the resulting confusion, when resolved, appeared to heighten student learning, particularly in relation to correcting the misconceptions. What is apparent from this research is that there seems to be a complex mix of factors that lead to students experiencing difficulties and uncertainty about what kinds of outcomes occur as a event. The factors vary betwixt students and the kinds of difficulties faced will differ across knowledge domains and task types.

From these few studies it is evident that experiencing difficulties and confusion might be beneficial for different students nether different circumstances and that the role of confusion in productive learning is important to understand beyond dissimilar learning environments, noesis domains, and types of learning activities. Dweck'south (1986) work indicates that confusion may be interpreted, managed and adjusted to in different means past students depending on their levels of confidence and past achievements. On the other mitt, the work of D'Mello et al. (2014) and Chen et al. (2013) suggests that defoliation tin can help students' learning, specially when conceptual learning or conceptual modify is the aim of the action.

In this integrative review, we examine the literature on difficulties in learning. We focus here on the ways in which it might be possible to detect confusion experienced every bit a result of difficulties and intervene when students are counterproductively confused. Our aim is to explore the ways in which the difficulties students experience in learning could be harnessed for the purpose of enhancing their didactics. If digital learning environments are to reach their potential, they must be designed in a manner to enable sophisticated support and feedback to dislocated students, in ways that are like to those a teacher can provide in pocket-size group face-to-face settings.

Difficulties, Confusion, and Their Role in Learning

While confusion is common in educational exercise and learning research, mostly speaking, it has been poorly defined and understood in the educational literature (Silvia, 2010). Confusion is frequently associated with reaching a cerebral impasse or "being stuck" while trying to larn something new (Woolf et al., 2009), and it is also usually regarded as a negative emotional experience or something to be avoided while learning ("Miss, assistance me, I am dislocated!"; see too Kort et al., 2001). Both of these aspects of confusion—existence stuck and a feeling to exist avoided—accept perhaps led to the everyday notion that confusion is detrimental to learning. While there is certainly research that suggests when confusion persists to the indicate of frustration, information technology normally leads to negative outcomes and has a detrimental bear on on understanding (Dweck, 1986; D'Mello and Graesser, 2011), as mentioned above, there are times when it may be benign to feel a cerebral impasse and the feeling of defoliation when learning.

When it comes to defining what defoliation really is, at that place has been some ambiguity as to the extent to which it is a cerebral or emotional phenomenon (D'Mello and Graesser, 2014). This doubtfulness stems from debates nigh whether or not emotions such as defoliation crave some element of interpretation in guild for the subjective experience of the emotion to accept form. These views are derived from an attributional perspective on emotion (Schachter and Singer, 1962). The process, co-ordinate to this perspective, is that confusion is the result of an individual's attribution of an affective response to a preceding subjective feel. In other words, the student reaches an impasse that causes them some difficulty. As a outcome of the impasse, the student has some sort of emotional response to the situation they find themselves in. That emotional response is then interpreted by the private—they attribute meaning to it—which may exist confusion (or anxiety, or excitement). In this way, the individual experiences or "attributes" the emotion of confusion to the impasse. This interpretation is particularly of import given that confusion in learning needs to be about some educational material attempting to be understood by a pupil (Silvia, 2010). Nonetheless, the attributional process also suggests that there are substantial differences betwixt individuals in terms of the attributions they make. Two students tin can experience the verbal same educational weather condition and interpret them in vastly unlike ways, leading i to be confused while the other experiences no such response. The interaction between subjective experience and content knowledge has led to confusion being defined every bit an "epistemic emotion" (Pekrun and Stephens, 2011). In other words, confusion can be defined as an affective response that occurs in relation to how people come to know or empathize something. When defined as an epistemic emotion, confusion is considered to have both cerebral and melancholia components.

While it is reasonably articulate that defoliation has both cerebral and affective components, what is less obvious is whether difficulties in learning that result in confusion are productive or unproductive in learning. The literature in this surface area is somewhat equivocal. D'Mello et al. (2014) examined students when learning about scientific reasoning using an intelligent tutoring system. Past inducing confusion through the presentation of contradictory data, they were able to determine whether the feel of beingness dislocated contributed negatively or positively to learning outcomes. Two virtual agents were used in the intelligent tutoring system to nowadays information almost the topic. In the confusion condition, the information from the ii agents was contradictory and thus confusing for students. D'Mello and colleagues establish that when students completed the "confused" (i.e., contradictory) condition compared to when they completed the control (i.e., non-contradictory) condition they showed enhanced performance, and as a result, argued that confusion can be beneficial for learning. What remains unclear though is whether information technology was the difficulty, the subjective experience of confusion or a mixture of both that was responsible for the observed differences between the groups.

Numerous attempts have been made to induce difficulties and confusion during learning to make up one's mind under what weather it contributes productively to pupil learning outcomes (eastward.g., Lee et al., 2011; Lehman et al., 2013; Andres et al., 2014; Lodge and Kennedy, 2015). For example, Grawemeyer et al. (2015) examined students' confusion (and other emotions) during an activity in a digital learning environs that focussed on fractions. They found that, when provided with the appropriate support at the correct time, in the form of feedback and educational activity, the difficulties experienced by students led to enhanced learning. Similarly, Muller et al. (2007) considered how videos including the presentation and subsequent correction (refutation) of a misconceived notion could create pupil confusion compared to videos which used more traditional didactic presentation methods. Students who watched physics videos using the refutation method were exposed to the most confusing aspects of the concepts at the offset of the video followed past an explanation of the commonly misconceived aspects of the content. Despite their higher levels of reported defoliation, students in the refutation status showed greater knowledge gains compared to students who watched the more traditional videos. Muller and his colleagues argued that these findings are related to the extra mental effort expended in trying to understand the material when information technology is disruptive.

These findings, and specially Muller et al.'southward (2007) interpretation of their results, suggests that, when students experience difficulties and defoliation, it may in fact serve every bit a trigger to assist them overcome whatever conceptual obstacles they encounter during their learning. Forth similar lines, Ohlsson (2011) argues that impasses and difficulties experienced in the learning procedure could be effective triggers for students to rethink their learning approaches. When students reach a conceptual impasse, this may serve as a cue that their current strategy or approach to the learning material is non effective, leading them to consider alternate strategies (D'Mello and Graesser, 2012). This perspective is consequent with research that has considered students' strategies for dealing with challenging material. In a series of experimental studies, Change et al. (2007) constitute that, when difficulties are introduced while people learn and reason nigh new data, it triggers a shift in strategy, activating a more systematic or analytic approach to the material. It may exist, therefore, that difficulties encountered during the learning process that are accompanied past a subjective feeling of confusion can lead students to change their learning strategies which may resolve the impasse, resulting in learning benefits. What this inquiry and the findings suggest, even so, is that students need to be able to identify the trigger equally a cue to change strategy, which necessitates a capacity for monitoring and self-regulation.

Findings from other studies have found that defoliation-inducing difficulties are not a productive part of the learning process despite the empirical research supporting the notion that confusion is beneficial in students' learning. For example, Andres et al. (2014) examined defoliation while students engaged with a problem solving-based video game designed to aid them acquire about physics. In this study, confusion negatively impacted on students' ability to solve the problems and, compared to students who were less dislocated, confused students were less likely to principal the learning material. A 2d study, Poehnl and Bogner (2013), presented alternative scientific conceptions to a large group of ninth form students. Despite the evidently college levels of confusion in this group compared to a group who were not exposed to the confusion-inducing alternate conceptions, this group performed worse in terms of the overall number of conceptions learned. As such, there is alien evidence near what role difficulties and resulting confusion play in learning under dissimilar conditions. Given the possibility that defoliation may operate as a trigger for activeness. This over again highlights the possible part of self-regulation in this process. Year 9 students in the Poehnl and Bogner study may not take the same capacity to self-regulate their learning every bit university students in the other studies discussed here.

Perhaps surprisingly, these are amongst the few empirical investigations to directly consider the bear on of confusion on students' learning that have found it has a deleterious effect and those that have often involve younger students. However, research from other areas of learning and instruction, while non directly considering the part of defoliation in learning, accept provided findings that are relevant to the function that difficulties and confusion may play in students' learning. The of import distinction seems to exist the difference betwixt difficulties that students experience and the emotions that they experience every bit a result of these difficulties. While in that location has been limited research examining students' experiences of defoliation, there has been much work done on trying to empathize the role of difficulties in the learning process. For this review, we scanned the literature in educational psychology, experimental psychology, and teaching to expect for concepts that share a family resemblance (equally per Wittgenstein, 1968) to the enquiry on difficulties and confusion.

Research on Learning Challenges and Difficulties

Prominent amid like bodies of work that may assistance in understanding how difficulties might contribute to learning in digital environments is research in areas such equally desirable difficulties (e.g., Bjork and Bjork, 2011), productive failure (e.g., Kapur, 2008), impasse-driven learning (e.g., VanLehn, 1988), cognitive disequilibrium (e.g., Graesser et al., 2005), and investigations of learning in discovery-based environments (e.g., Moreno, 2004; Alfieri et al., 2011). It is amongst these cognate fields of enquiry that nosotros may find farther evidence to support the processes that pb to confusion being beneficial (or not) for learning. Our aim in attempting to compare and contrast this literature is to ameliorate understand how difficulties and confusion may be benign to learning and under what conditions.

Studies of desirable difficulties typically consider how aspects of the learning procedure can encumber learners, and how this procedure (or "difficulty") can lead to enhanced learning compared to learners not exposed to the difficulty (Bjork and Bjork, 2011). For instance, Sungkhasettee et al. (2011) asked participants to study lists of words either upright or inverted. When learning the inverted words, participants demonstrated superior recollect to conditions where the words were presented upright. In a similar study using more educationally relevant material, Adams et al. (2013) reported on a series of studies where erroneous examples were given to students who were learning mathematics in a digital environment. Across these studies, Adams et al. plant that the use of erroneous examples in mathematics instruction led to improvements in learning consequent with those observed in the broader literature on desirable difficulties. In order to describe the mechanism by which difficulties enhance learning, Adams et al., argue that the apply of incorrect examples encourages students to procedure the learning fabric in a different manner, which leads to amend retention and transfer of their understanding. They suggest that students, by considering and engaging in alternative problem solutions, process material more deeply and this is idea to exist responsible for the enhanced learning observed (meet also McDaniel and Butler, 2011).

The growing body of inquiry on desirable difficulties has raised some questions almost what constitutes a benign difficulty in the learning process (Yue et al., 2013). For instance, in a widely cited study, Diemand-Yauman et al. (2011) presented textile to participants (report 1) and students (report 2) in piece of cake and hard to read fonts. They found that participants and students who studied material in hard to read fonts performed better when later quizzed on the material. The authors hypothesized that the difficulty in reading the disfluent font slowed the learning process down, leading to deeper encoding, thus creating a desirable difficulty. Subsequent attempts to replicate this disfluency-based desirable difficulty have failed (e.thousand., Rummer et al., 2016), creating further uncertainty about what constitutes a desirable difficulty. Whatever the purlieus conditions of desirable difficulties, it is credible that sure kinds of difficulties in the learning process can reliably enhance the encoding, storage and retrieval of information. Participants exposed to desirable difficulties in the majority of the enquiry on these furnishings to engagement accept done so predominantly under laboratory weather condition. Nonetheless, it is apparent that there were substantial advantages to introducing targeted difficulties in the learning procedure that are strong candidates for enhancing learning in live educational settings (Yan et al., 2017) and for further explaining how difficulties contribute to quality learning more broadly.

The principle of productive failure provides another possibility for framing the utilize of difficulties to heighten learning. Productive failure is a way of sequencing learning activities to give students an opportunity to familiarize themselves with a complex problem or result in a structured surroundings simply without significant instruction on the content of the material to be learned (Kapur, 2015). Kapur (2014) tested groups of students who were given an opportunity to solve mathematics bug either before or after being given explicit didactics on the procedure associated with how to solve the problems. He found that the group of students who were given the opportunity to attempt problems before being given explicit instructions, despite ofttimes failing in their first attempts, overall demonstrated significantly greater gains in learning compared to students who received instructions prior to attempting to solve problems. Without necessarily having the requisite skills or data to solve the issues they were presented with, students would often reach an impasse in the learning process. Kapur (2015) argued that the impasse reached through the failed attempts at learning helps students generate more and different problem-solving strategies through a process that enhances learning over both the shorter and the longer term. It should be noted here that the tasks used in productive failure studies are dissimilar to those used in studies of desirable difficulties. Studies on productive failure tend to use more realistic problems given to students rather than tasks that rely more on memorisation.

Despite the different kinds of tasks used, there are clear parallels between the "failure" aspect of productive failure, and the "difficulties" encountered by students within a desirable difficulty paradigm (Kapur and Bielaczyc, 2012). In both situations, at that place is a deliberate strategy to encumber students' learning process and potentially trigger confusion. Unlike the work on desirable difficulties, however, much of the inquiry on productive failure has been carried out in naturalistic educational settings. This is achieved partly through the sequencing of the activity. The lack of direct teaching on the trouble or issue often leads students to inevitably reach an impasse in the learning process that is seemingly accompanied by a sense of defoliation (Hung et al., 2009). As summarized by Kapur (2015), the benefits of productive failure have been demonstrated many times in the peer-reviewed literature (e.thou., Kapur, 2008; Kapur and Rummel, 2012). The results of these studies demonstrate that when students engage in some problem solving kickoff followed by but-in-time didactics when they reach an impasse (i.e., the process leads to failure), it leads to enhanced learning in educational situations that are designed to rely on direct instruction.

Productive failure shares some similarity with the notion of impasse-driven learning, which focuses on what happens when students attain a blockage in their learning. VanLehn (1988) suggests that when students attain an impasse in the learning process, it forces them to go into a problem-solving strategy he labeled "repair." In other words, students engage in a metacognitive process whereby they endeavour to employ trouble-solving strategies to overcome the impasse or seek help. In both cases, the necessity of engaging in "meta-level" thinking is hypothesized to lead to more than constructive learning. This notion is similar to the argument fabricated by Ohlsson (2011) in relation to strategy shifting and again highlights the importance of a capacity to monitor and self-regulate learning. In a examination of impasse-driven learning, Blumberg et al. (2008) examined frequent and infrequent players of video games and asked them to draw their experiences every bit they worked through a novel video game. They establish that participants who engaged in video games regularly were more able to describe their problem-solving strategies and moments of insight than those infrequently exposed to the types of impasses institute in the games. To examine how this process applies to tutoring, VanLehn et al. (2003) analyzed dialogue in tutoring sessions on physics. Their results suggested that students were receptive to tutoring particularly when they reached an impasse in the learning process compared to when they were not at an impasse. The inquiry on impasse-driven learning again suggests that there is something disquisitional about the metacognitive, learning or study strategies that students engage in when their learning procedure is disrupted or challenged in some style.

At the cadre of desirable difficulties, productive failure and impasse driven learning is the notion that a difficulty or deliberately designed challenges are of import for learning (VanLehn, 1988; Ohlsson, 2011). Gimmicky, and increasingly popular models of pedagogy, rooted in Bruner's (1961) notion of discovery-based learning also share this feature. Discovery-based models of teaching and learning such as trouble-based learning typically present students with an ill-structured scenario, situation or problem, which they discuss, often in groups, and investigate in order to resolve. Students, in discussing the problem among themselves with or without a more expert facilitator, inevitably encounter material that they do non understand, that is disruptive, and represents an impasse in their investigation of the trouble. These impasses are central to the problem-based learning instructional model equally they both bulldoze the learning process (condign the "learning problems" that guide students' learning and guide their investigations of the problem) and they likewise are said to act as intrinsic motivators for students equally they attempt to resolve the problem (Schmidt, 1993).

Given some of the core similarities betwixt these theoretical models,—productive failure, impasse driven learning, desirable difficulties, and problem-based learning—a key question for educational researchers is: what are the underlying cognitive and learning processes that both bring nigh educatee confusion, and underpin the potential learning benefits derived from it? Also, how do these processes differ betwixt individual students, learning different textile, and engaged in different types of tasks? Graesser and D'Mello (2012) suggest that the prime candidate for this underpinning process is cognitive disequilibrium. The notion of cognitive disequilibrium is derived from Piaget's piece of work on cognitive development (Piaget, 1964). It occurs when in that location is an imbalance created when new data does not seamlessly integrate with existing mental schema. It is plausible then that confusion is the consequence of certain types of difficulties in the learning process, namely those that atomic number 82 to an impasse underpinned by cognitive disequilibrium. In attempting to design for and provide interventions for productive challenges then, what appears to exist important is not the introduction of difficulties per se but the introduction of difficulties that lead to an impasse and a sense of disequilibrium. Based on the research across these domains this, in turn, is hypothesized to atomic number 82 to a change in learning arroyo or problem-solving strategy that tin can raise learning.

A Framework for Agreement and Seeing Difficulties and Resulting Confusion in Learning

From this review, it seems clear that difficulties experienced during learning and resulting in defoliation tin can be either productive or unproductive depending on the arrangement of and human relationship between a range of variables within a learning environment. These include the type of learning action, the knowledge domain being learned, and individual differences such as how students attribute difficulties and their chapters for self-regulated learning. For whatever particular learning or content surface area, the caste to which difficulties are experienced by a learner, and whether the experience of the resulting epistemic emotion will be productive or unproductive, is a result of a complex human relationship betwixt:

(i) Individually-based variables, such as prior knowledge, self-efficacy, and self-regulation;

(ii) The sequence, structure and blueprint of learning tasks and activities; and

(iii) The pattern and timeliness feedback, guidance, and back up provided to students during the learning activity or task.

A cardinal challenge for educational researchers is to decide what sets of relationships betwixt what variables lead to adaptive and maladaptive learning processes and outcomes in digital learning environments.

The review of the literature also suggests 2 learning processes could be promoted when students experience confusion: i general and ane specific. The first, more general, process is that difficulties encourage students to invest more "mental effort" in their learning; they somehow work harder cognitively—through attention or concentration—to resolve the conceptual impasse and the confusion that has resulted from it. The 2d is that students, when piqued by a conceptual impasse and the resulting feelings of confusion, actively generate and prefer alternative approaches to the learning material they are seeking to understand. This second process suggests that students do not simply invest a greater effort in their learning; it suggests that they investigate and adopt alternative study approaches and strategies, which they then apply. In order for this second process to occur, students need to be sufficiently able to monitor their progress and sympathize how to accept activeness on the ground of their experience of difficulty or the reaching of an impasse.

Finally, this review suggests that insurmountable learning difficulties may arise when students experience besides much defoliation or when defoliation persists for too long. As discussed by D'Mello and Graesser (2014) i of the most important factors in the beneficial effect of confusion is that information technology is resolved. Unresolved, persistent confusion leads to frustration, boredom and therefore is detrimental for learning. In an example of this delicate balance in activeness, Lee et al. (2011) examined confusion while novices attempted to larn how to write computer code. They found that overcoming confusion tin can enhance learning but, when it remains unresolved, it leads to deleterious effects on student accomplishment. This observation speaks to the importance of addressing pupil confusion in a timely and personalized fashion. Even so, given the complexities introduced by the individual differences between students, this is not a straightforward task.

In many means, these features of defoliation are captured in Graesser's (2011) notion of a "zone of optimal confusion" (ZOC). Reminiscent of Vygotsky's (1978) concept of the zone of proximal development, the ZOC suggests that information technology is important not to accept too footling or too much difficulty but to aim to have merely the right amount. If educators and educational designers aimed to create challenges and induce a modify in learning strategy as a deliberate tactic to promote conceptual change, students would need to experience sufficient subjective difficulty for the impasse in the learning process to be experienced equally defoliation. However, if likewise much or persistent confusion is experienced, information technology volition pb to frustration, hopelessness, boredom and giving upwardly. To use difficulties as a deliberate instructional strategy in digital learning environments is, therefore, a double-edged sword. If students are non sufficiently engaged to become dislocated and redress their way of approaching the activeness, they can then become bored and potentially regress back to their initial formulation. If students can be guided and supported through their confusion, nevertheless, it tin can then lead to the productive learning outcomes reported in the empirical literature. That, in essence, is the ZOC.

One ongoing upshot with the notion of "optimal confusion" is that it is hard to determine what separates productive from non-productive defoliation every bit learning unfolds. Given the complexities involved due to individual responses to difficulties in learning, the threshold at which effective confusion becomes not-productive frustration or boredom volition differ markedly between individuals (Kennedy and Lodge, 2016). Identifying where a student might be along the defoliation continuum in advance of knowing the outcome of the learning activity is a significant challenge. Kennedy and Society constitute that there were markers axiomatic in trace data suggestive of students crossing the threshold into unproductive forms of defoliation. For example, extended delays in progress observed equally significant fourth dimension lags between interactions or rapid cycling through activities are possible indicators of boredom or frustration respectively. Inferring in real time whether students are experiencing defoliation that is productive or unproductive remains a challenge but there is some emerging bear witness that data and analytics could be used to aid predict how students are tracking and provide feedback and support contained of knowing the upshot (Arguel et al., 2019).

Based on Graesser'south (2011) "ZOC" and, using cognitive disequilibrium every bit a framing mechanism for the important office of confusion in learning, nosotros propose a framework for confusion in digital learning environments (see Figure 1). From the top of Figure one, a learning event can exist specifically designed to create cognitive disequilibrium. An example of this is the approach used past Muller et al. (2008) to create disequilibrium in videos. In this study, the researchers created disequilibrium past focussing on misconceptions as a core instructional strategy, the disequilibrium existence generated through the altitude between what people think they know and the accustomed scientific understanding. From in that location, disequilibrium is generated as a cause of an impasse in the learning process. At this stage, students will move into the ZOC so long as they are sufficiently engaged and attribute the impasse to be confusing. If this occurs in a productive manner and the student has sufficient metacognitive awareness and skill to recognize the confusion as a cue to change strategy, the disequilibrium will be finer resolved, conceptual change volition occur, and students will move on to some other learning issue. If the confusion becomes persistent, on the other hand, then students may possibly movement into the zone of sub-optimal confusion (ZOSOC). When this occurs, the confusion becomes unproductive and leads to possible frustration and/or boredom. Again, it is hard to decide in real time when and how this occurs and that remains a challenge for future research to examine. The model proposed here builds on similar previous piece of work by D'Mello and Graesser (2014) simply is specially focused on further elucidating both the underpinning processes and the characteristics of the learning pattern that might influence both the initiation of confusion and its resolution.

Figure 1. Conceptual framework for the zones of optimal and sub-optimal confusion.

Implications of the Framework

If it tin be causeless that defoliation is beneficial for learning nether some circumstances and so it is worth considering the implications of this for learning design. The cosmos of disequilibrium and confusion is important to both appoint students and create the uncertainty required to assistance them develop conceptual knowledge. A learning event that is aimed at creating this disequilibrium will need to be designed with the aim of both getting students into the ZOC and making sure that they practise non enter the ZOSOC. Enticing students to enter the ZOC has been accomplished in numerous means as described above. For case, the fabric presented or the medium through which information technology is presented can exist contradictory, counterintuitive or the environs can have trivial to no guidance as in pure discovery-based learning and, to a lesser extent, productive failure. Taken together, there would appear to exist many means to lure students into the ZOC. That said, in that location are no guarantees that students will enter this ZOC. If a student has high levels of prior knowledge or is highly confident, for example, they may persist at a task with renewed vigor rather than attribute an impasse as confusing (Arguel et al., 2016).

When it does occur, ensuring the defoliation leads to a productive outcome is more challenging as it requires the students themselves resolving the disequilibrium, a timely intervention from a teacher, or in a style that can exist automatically supported in a digital learning environment. Thus, there appear to be 2 broad options for ensuring confusion leads to productive outcomes. As alluded to above, the development of effective self-regulation in learning is one way of ensuring that students move from beingness confused to effectively learning. While students' skills in self-regulation are something they may at least partly bring to a learning event, there is likewise potential for edifice in interventions to assist with self-regulation into the learning environment (Club et al., 2018). For example, if students did modify their strategy or arroyo to a learning event, this creates an opportunity for them to reverberate on the change in their approach and consider how such a strategy might be useful in time to come learning situations. So, while there are opportunities for helping students to effectively learn new material, there are also possibilities in these situations for students to consider the strategies they employ when learning more broadly. In a very concrete mode, one intervention strategy is to help students to understand that difficulties and confusion every bit part of the learning process are perfectly normal and, indeed, necessary in many instances. Helping students to come across confusion equally a cue to endeavour a unlike approach rather than see it is a sign that they are incapable would be a simple way to improve students' chapters to deal with difficult and confusing elements of learning.

A second option for ensuring that students finer pass through the ZOC and accomplish productive learning outcomes is to employ feedback. Feedback can have many different forms in digital learning environments thus providing many options for intervening when students appear to exist dislocated. The disquisitional aspect of any intervention on confusion to avoid having students enter into the ZOSOC will be to personalize that feedback by taking into business relationship their prior knowledge (Lehman et al., 2012). Intelligent tutoring systems have some chapters for this level of personalisation. However, much remains to exist done earlier these systems can be regarded as being truly adaptive to the affective components of student learning and applied at scale (Bakery, 2016). As a proof of concept though, there are examples of sophisticated adaptive systems that have been congenital to provide real time feedback and prompts based on student performance as they progress through procedural tasks. For example, adaptive systems take long been bachelor to provide data-driven feedback and prompts to trainee surgeons (Piromchai et al., 2017), and dentists (Perry et al., 2015). That it is possible to create systems that can use data most student interaction to inform feedback interventions propose that information technology is possible to build systems that volition work beyond different knowledge domains to reply to students having difficulties.

In the acting, while intelligent tutoring and other adaptive systems built on automobile learning and bogus intelligence mature, at that place are possibilities for building digital learning environments to cater for difficulties and resulting confusion. Near prominent amongst these are the evolution of sophisticated learning designs that tin respond to educatee confusion through enhancing pupil self-regulation and providing feedback in the class of hints or determinative information about the strategies or approaches being used. That is not to say that the evolution of such systems volition be like shooting fish in a barrel. Part of the approach to helping students become better equipped to deal with difficulties and confusion needs to be to address the notion that difficulties are inherently detrimental and an indicator that students are not capable.

Conclusion

Difficulties and the confusion that frequently results are difficult to detect, manage, and respond to in digital learning environments and large classes compared to smaller grouping face-to-face settings. Despite this, in this paper nosotros have argued that difficulties and defoliation are important in the process of learning, particularly when students are developing more than sophisticated understandings of complex concepts. Work on desirable difficulties, impasse driven learning, productive failure, and pure discovery-based learning all provide clues as to how confusion could exist beneficial for learning. The cosmos of a sense of cognitive disequilibrium appears to be a vital element and the confusion needs to be effectively resolved by helping students pass through the ZOC without them entering the ZOSOC. Nosotros have attempted here to provide a conceptual model for the process by which students pass through this optimal zone. Our hope is that this will assist to outline the procedure of the evolution and resolution of confusion so that researchers and learning designers can continue to develop methods for ensuring students attain productive outcomes as a effect of becoming dislocated.

Author Contributions

JL, GK, LL, AA, and MP contributed to the conceptualization, research, and writing of this article.

Funding

The authors of this review received funding from the Australian Research Council for the work in this review equally function of a Special Enquiry Initiative (Grant number: SRI20300015).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could exist construed every bit a potential conflict of interest.

Acknowledgments

The authors acknowledge the contributions of Dr. Paula de Barba toward this project.

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