Topic Blog 4: A Final Review of Effective Tutoring Systems.

Topic Blog 4: A Final Review of Effective Tutoring Systems.

As a reminder from my other blog post; In 1984 Benjamin Bloom did a study in which it was discovered that on average, students that were tutored learned more than their in-class peers, and often had “great differences in cognitive achievement, attitudes, and academic self-concept” (Bloom, 1984). Since then there have been many different methods and approaches when it comes to tutoring; all of which have a significant increase in student performance when compared to just learning from class material.

Today, there are several forms of tutoring. However, there are three approaches that are the most popular. The first is human tutoring, which is usually described as an adult professional working directly with a student. The second is peer tutoring, where a higher academically achieving student is paired with a lower achieving student, where they review topics and areas of struggle in attempt to improve grades and performance. The last being intelligent tutoring systems (ITS), where a computer system aims to provide a unique response tailored to the user/learner.

The human tutoring approach has its main successes in the tutors ability to make detailed diagnostic assessments, where they can judge where a student stands in terms of subject comfortability, and supply additional assistance as well as adapt their tutoring style to better suit the needs of the individual student (VanLehn, 2011). Another valuable factor in human tutoring is the use of sophisticated tutorial strategies, such as Socratic irony, the inquiry method, and reciprocal teaching.

Peer tutoring on the other hand, has main successes of peer tutoring is due to its applicability where many subjects, such as reading, math, social studies and science, can all be taught and expanded upon by the tutors (Bowman-Perrott, et al.,2013), as well as its mutual benefits, where the tutee is able to clarify questions with almost instantaneous responses and the tutor is able to solidify and pass-on their understanding. Another study by Liesje De Backer, Hilde Van Keer and Martin Valcke suggests that there is a direct correlation between the sociality of peer tutor groups and metacognitive regulation. This is believed to be due to the “fruitful environment for eliciting and optimising collaborative learners regulative acts at the social level” (Backer, Keer & Valcke,. This coincides with the mutual benefits proposed by Bowman-Perrott and colleagues.

A study by Van Lehn explains that the success of ITS comes from the program facilitating “self-repair” in the student’s knowledge, and from the scaffolding technique that is employed where hints are given when a student is stuck on a problem. Van Lehn also points out that many programs do not allow a student to advance to the next question unless the question is answered correctly, forcing the student to focus and solve the current problem (Van Lehn, 2011). ITS can mostly be classified into two main categories, the first is “Step-Based tutoring”, where a student would work using the same steps they normally would without the tutoring system (such as math equations, or balancing chemical formulas), but can ask for and receive “hints” or “advice”, depending on the program (Van Lehn, 2011). The second is “Substep-Based tutoring”, which can use more effective and advanced tutoring techniques such as the scaffolding technique and constructive feedback. There is a third category I’ll briefly mention known as “Answer-Based” programs, where the tutee-tutor-system interaction is extremely limited to when the student enters the answer, and the system judges if its correct or not without any additional assistance allowed, where the user is assumed to have reasoned through it all by themselves. This system is very ineffective.

In conclusion: Human tutoring has always been perceived as being the most effective form of tutoring, but as of recent, the ITS and peer tutoring systems have challenged that perception. In the end, some form of tutoring is better than none. 🙂 thanks for reading.

 

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16.

Bowman-Perrott, L., Davis, H., Vannest, K., Williams, L., Greenwood, C., & Parker, R. (2013). Academic benefits of peer tutoring: A meta-analytic review of single-case research. School Psychology Review42(1), 39.

De Backer, L., Van Keer, H., & Valcke, M. (2015). Exploring evolutions in reciprocal peer tutoring groups’ socially shared metacognitive regulation and identifying its metacognitive correlates. Learning and Instruction38, 63-78.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.

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Topic Blog 3: Further Analysis of Tutoring; Intelligent Tutoring Systems.

Topic Blog 3: Further Analysis of Tutoring; Intelligent Tutoring Systems.

My blog posts over the last few weeks have been about peer tutoring, and human tutoring as effective tutoring strategies. To wrap up my topic blogs, the final tutoring approach I’ll be discussing is the use of intelligent tutoring systems (ITS), how they compare to human tutoring and the reasons behind their supplementary advantages to regular class-based education.

As a reminder from my other blog post; In 1984 Benjamin Bloom did a study in which it was discovered that on average, students that were tutored learned more than their in-class peers, and often had “great differences in cognitive achievement, attitudes, and academic self-concept” (Bloom, 1984). Since then there have been many different methods and approaches when it comes to tutoring; all of which have a significant increase in student performance when compared to just learning from class material.

Bloom based his study exclusively off of human tutoring, but there has been recent studies indicating that intelligent tutoring systems are very close in matching the overall effectiveness of the human tutoring approach. A 2011 review by Kurt Van Lehn rates effective tutoring methods, finding that human tutoring and ITS were almost even in terms of effectiveness, with d=0.79 and 0.76 respectively. Another study by Ma and colleagues found that there was very little difference between “learning from an ITS and learning from individualized human tutoring” (Ma et al., 2014).

Van Lehn explains that the success of ITS comes from the program facilitating “self-repair” in the student’s knowledge, and from the scaffolding technique that is employed where hints are given when a student is stuck on a problem. Van Lehn also points out that many programs do not allow a student to advance to the next question unless the question is answered correctly, forcing the student to focus and solve the current problem (Van Lehn, 2011).

ITS can mostly be classified into two main categories, the first is “Step-Based tutoring”, where a student would work using the same steps they normally would without the tutoring system (such as math equations, or balancing chemical formulas), but can ask for and receive “hints” or “advice”, depending on the program (Van Lehn, 2011). The second is “Substep-Based tutoring”, which can use more effective and advanced tutoring techniques such as the scaffolding technique and constructive feedback. There is a third category I’ll briefly mention known as “Answer-Based” programs, where the tutee-tutor-system interaction is extremely limited to when the student enters the answer, and the system judges if its correct or not without any additional assistance allowed, where the user is assumed to have reasoned through it all by themselves. This system is very ineffective.

In another study, Ma and colleagues state in their results that ITS was a benefit “regardless of whether it was used as the principal means of instruction, as an integral part of classroom instruction, to support in-class activities such as laboratory exercises, for supplementary after-class instruction, or as part of assigned homework” (Ma et al.,2014).

In conclusion: while ITS isn’t quite as popular as it use to be, advancements in computer technology and human understanding of education have given ITS a second chance, shining a new light on these programs which have been proven to be just as effective as the human tutoring effect Bloom originally witnessed.

Thank you for reading. 🙂

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16.

Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.

Topic Blog 2: Further Analysis of Tutoring; Human Tutoring.

Topic Blog 2: Further Analysis of Tutoring; Human Tutoring.

To build on my decision to further analyze tutoring approaches, this week I’ll be focusing on human tutoring. During my talk yesterday it was brought up that there is no clear distinction between peer tutoring and human tutoring. I did some research and I’ll be working off of Kurt VanLehn’s 2011 definition which states; “human tutoring refers to an adult, subject matter expert working synchronously with a single student. This excludes many other kinds of human tutoring, such as peer tutoring, cross age tutoring, asynchronous online tutoring (e.g., e-mail or forums), and problem-based learning where a ‘tutor’ works with a small group of students” (VanLehn, 2011).

As a reminder from my other blog post; In 1984 Benjamin Bloom did a study in which it was discovered that on average, students that were tutored learned more than their in-class peers, and often had “great differences in cognitive achievement, attitudes, and academic self-concept” (Bloom, 1984). Since then there have been many different methods and approaches when it comes to tutoring; all of which have a significant increase in student performance when compared to just learning from class material. As of recent, ITS (intelligent tutoring systems) have become just as, if not more useful and efficient in promoting student learning, challenging Blooms original study of human tutoring being the most effective. I’ll be examining ITS systems next week, so stay tuned for that! 😉

The human tutoring approach has its main successes in the tutors ability to make detailed diagnostic assessments, where they can judge where a student stands in terms of subject comfortability, and supply additional assistance as well as adapt their tutoring style to better suit the needs of the individual student (VanLehn, 2011). Another valuable factor in human tutoring is the use of sophisticated tutorial strategies, such as Socratic irony, the inquiry method, and reciprocal teaching.

There are some slight drawbacks to the human tutoring approach, such as cost, inability to assess the student’s skill range, and occasionally the inadequate mastery of the tutor themselves . Private tutors average around $30-40 an hour, but can be more expensive depending on the tutor. While even the average price would be considered expensive, there has been research done in English tutoring where “given that tutoring cost is determined by the price in the market, the quality of the service is likely to be reflected in the cost” (Kim et al., 2016). In terms of the inability to assess the student’s skill level; tutors are often hindered in their instruction when a student has pre-existing misconceptions, false beliefs, and buggy skills that interfere with the tutors ability to build and expand on learning material (Van Lehn, 2011).

In conclusion; human tutoring has reigned at the most effective form of tutoring, but recently has be equalled and occasionally surpassed by different ITS systems. The human tutoring approach still excels in the ability to assess students true comfortability with material, but can sometimes fail if the tutor isn’t skilled enough to impart a better understanding onto the student.

Thanks for reading! 🙂

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.

Kim, M. S., Paik, I. W., & Ihm, J. J. (2016). Do time and cost students spend on private tutoring contribute to improving their achievement in English and Mathematics?. KEDI Journal of Educational Policy, 13(2).

Topic Blog 1: Further Analysis of Tutoring; Peer Tutoring.

Topic Blog 1: Further Analysis of Tutoring; Peer Tutoring.

Two weeks ago I posted about different tutoring approaches, quickly summarizing the three most popular styles of educational assistance. I decided that I could go more indepth into the tutoring topic by doing my topic blog sets on those three tutoring approaches. This blog marks my first Topic Blog; Peer tutoring.

As a reminder from my other blog post; In 1984 Benjamin Bloom did a study in which it was discovered that on average, students that were tutored learned more than their in-class peers, and often had “great differences in cognitive achievement, attitudes, and academic self-concept” (Bloom, 1984). Since then there have been many different methods and approaches when it comes to tutoring; all of which have a significant increase in student performance when compared to just learning from class material.

A 2013 meta-analysis defines peer tutoring; “a class of practices and strategies that employ peers as one-on-one teachers to provide individualized instruction, practice, repetition and clarification of concepts”(Bowman-Perrot, et al., 2013). Of the three tutoring approaches (human tutoring, peer tutoring, and intelligent tutoring systems), its well known that human tutoring and ITS systems are the most efficient at improving students grades. Peer tutoring can also be very effective as well, given that they’re studying the right material and understand it, as well as stay on task.

The main successes of peer tutoring is due to its applicability where many subjects, such as reading, math, social studies and science, can all be taught and expanded upon by the tutors (Bowman-Perrott, et al.,2013), as well as its mutual benefits, where the tutee is able to clarify questions with almost instantaneous responses and the tutor is able to solidify and pass-on their understanding. Another study by Liesje De Backer, Hilde Van Keer and Martin Valcke suggests that there is a direct correlation between the sociality of peer tutor groups and metacognitive regulation. This is believed to be due to the “fruitful environment for eliciting and optimising collaborative learners regulative acts at the social level” (Backer, Keer & Valcke,. This coincides with the mutual benefits proposed by Bowman-Perrott and colleagues.

In conclusion, the more social approach of peer tutoring is much more beneficial than studying alone, if you’re capable of staying focused and have the ability to contribute meaningfully to the discussion.

Thanks for reading! 🙂

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16.

Bowman-Perrott, L., Davis, H., Vannest, K., Williams, L., Greenwood, C., & Parker, R. (2013). Academic benefits of peer tutoring: A meta-analytic review of single-case research. School Psychology Review42(1), 39.

De Backer, L., Van Keer, H., & Valcke, M. (2015). Exploring evolutions in reciprocal peer tutoring groups’ socially shared metacognitive regulation and identifying its metacognitive correlates. Learning and Instruction38, 63-78.

The Weight of Student Loans; More Than Financial Debt.

The Weight of Student Loans; More Than Financial Debt.

Student debt. Something we can all relate to, and something we all hope to pay off. With the cost of post secondary education on a unfair, and exponential rise, the pressure for students to complete a degree and pay off the debt is greater than ever before. The obvious financial pressures aside, what are the other costs students in debt face? The purpose of this weeks blog is to discuss the effects of student debt on those seeking higher education.

I’d like to start this post off by stating how ridiculous education costs today. Over the course of three decades post secondary education has increased by 250% (Baum & Ma, 2012), with “student debt in the U.S.A. now exceeding $1 trillion” (Doran et al., 2016). A large majority of the student debt (40%) in the U.S. can be contributed to students who pursue graduate degrees. A 2016 analysis on graduate psychology students by Jennifer Doran and colleagues found that the average student incurred a total (undergraduate and graduate) debt of $141,078.07 (Doran et al., 2016). That’s pretty crazy. You could buy a 2008 Lamborghini Gallardo Spyder with that money (I googled it).Screen Shot 2017-10-19 at 5.16.39 PM

In a 2015 research article by Claire Callendar and Geoff Mason predicted that the incredible amount of debt creates a debt-averse attitude, which is defined as “an unwillingness to take a loan to pay for college, even when that loan would likely offer a positive long-term return” ( Callendar & Mason, 2015). This attitude discourages low income students from pursuing a university or collage degree. One of the measures used to predict how debt-adverse a student is the wording used to describe financial aid. Financially equivalent choices were proposed to students, in which a “human capital contract” was chosen more readily in comparison to “loans” (Callendar & Mason, 2015).

Doran and colleagues go on to further assess the impact of student debt by using a Likert scale from 0-4 (“none at all”, to “extreme” respectively). Students were asked to rate their financial stress. 48.9% of students gave a significant rating of 3 or higher (Doran et al., 2016). Furthermore, the students were asked if their debt delays other life plans. 65.7% of students reported that their retirement planning was delayed, 62.5% stated that their plans for buying a home were delayed, and 49.3% of students believe their plans for having children and/or getting married were delayed (Doran et al., 2016).

In addition to the debt crisis students are facing, there is a strong link between financial difficulty and mental health. Richardson and colleagues predicted that undergraduate students that had greater financial struggles also were more prone to depression and anxiety, and had higher indices of alcohol dependence (Richardson et al., 2017). The results concluded that “greater stress about debt predicted greater anxiety, depression, stress and poorer global mental health” (Richardson et al., 2017). Conversely, the results found that students that were more financially stable were more likely to develop an alcohol dependency. The study mentions a ‘vicious cycle’ in its discussion, in which low mental health encourages intensifies financial instability, which then feeds to low mental health again (Richardson et al., 2017).

In conclusion; the rise of debt on students has more consequences than just prolonged payment. Students devote their life plans past graduation, and their mental health at the expense of student loans.

Thanks for reading! 🙂

Baum S., Ma J. (2012). Trends in college pricing. Trends in Higher Education Series. The College Board.

Callender, C., & Mason, G. (2017). Does student loan debt deter higher education participation? New evidence from England. The ANNALS of the American Academy of Political and Social Science671(1), 20-48.

Doran, J. M., Kraha, A., Marks, L. R., Ameen, E. J., & El-Ghoroury, N. H. (2016). Graduate debt in psychology: A quantitative analysis. Training and Education in Professional Psychology10(1), 3.

Richardson, T., Elliott, P., Roberts, R., & Jansen, M. (2017). A longitudinal study of financial difficulties and mental health in a national sample of British undergraduate students. Community mental health journal, 53(3), 344-352.

 

The Values of Tutoring; Comparing Tutoring Approaches.

The Values of Tutoring; Comparing Tutoring Approaches.

A few weeks ago I made a comment on Rachel’s blog and mentioned how hiring a tutor in high school became especially effective in helping me understand class material and encouraging me to -actually- complete my homework. This week I wanted to build on that and write about the different approaches to tutoring, and the respective values of each tutoring style as a supplement to education.

In 1984 Benjamin Bloom did a study in which it was discovered that on average, students that were tutored learned more than their in-class peers, and often had “great differences in cognitive achievement, attitudes, and academic self-concept” (Bloom, 1984). Since then there have been many different methods and approaches when it comes to tutoring; all of which have a significant increase in student performance when compared to just learning from class material.

A hypothesis formed on the significant success of students undergoing tutoring is known as the ‘Interaction Hypothesis’, in which the specific linguistic mechanics used by tutors are found to be especially effective (Albacete & Katz, 2013). The main drive behind tutoring and tutoring research is to discover what is the most effective and apply it to other areas of education so the vast majority can receive the same benefits that have been described by Bloom.

Today, there are several forms of tutoring. However, there are three approaches that are the most popular. The first is human tutoring, which is usually described as an adult professional working directly with a student. The second is peer tutoring, where a higher academically achieving student is paired with a lower achieving student, where they review topics and areas of struggle in attempt to improve grades and performance. The last being intelligent tutoring systems (ITS), where a computer system aims to provide a unique response tailored to the user/learner.

Of these three tutoring approaches, human tutors are believed to be the most effective in terms of aiding student learning, but advancements in computer technology and tutoring systems have placed these two methods as almost equals (VanLehn, 2011). One of the reasons why human tutoring is perceived to be more effective is due to the human ability to judge the students “competence and misunderstanding” of the material, and supply adequate and reasonable feedback almost immediately when said student incurs a problem. Another is the Scaffolding technique, in which the teacher/tutor builds directly and immediately on the students reasoning, creating constructive and understandable dialogue, which most ITS programs today lack. However, human tutoring lacks in its availability for every student, which is where ITS becomes a more convenient tutoring resource when compared to human tutoring (VanLehn, 2011).

Tutoring itself has become well established in educational settings, yet the ITS and peer tutoring approach still needs some much needed research and development to become more accessible and effective for all students.

Thanks for reading! 🙂

Refferences

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16.

Katz, S., & Albacete, P. L. (2013). A tutoring system that simulates the highly interactive nature of human tutoring. Journal of Educational Psychology, 105(4), 1126.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.

 

 

Gratification and Studying; “Good Things Come to Those Who Wait”.

Gratification and Studying; “Good Things Come to Those Who Wait”.

Millennials have been branded as a thankless generation; with cheap news headlines such as ‘Today’s generation demands instant gratification’. Statements like this lead the public to have a very sad and dismal view of the future when we come to inherit it. The main point behind this week’s blog is to discuss the importance of gratification in the classroom with today’s youth as the focus.

Many people have heard of the ‘Delayed Gratification’ experiment, in which children were given a marshmallow, and faced with the decision to eat it now, or wait ten minutes while the tester leaves and then returns to the room, and receive a second marshmallow. Walter Mischel at Stanford University performed the original experiment in the 1960’s, and videos of the experiment are often replicated on YouTube (They’re always super cute, so here are some links 1 2). In Mischel’s original experiment, the children that were able to resist the urge to eat the marshmallow were interviewed in their adolescence, showing higher competency in academic performances, higher tolerances to stress, better planning and reasoning skills, and maintained that same self control demonstrated as kids.

If you scroll through the Internet you’ll occasionally come across some modern twists to Mischels experiment created to this to help students maintain motivation; such as placing gummy bears on your textbook at the start of each new paragraph, earning the right to eat them as you make progress through your readings.

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Despite what is said about millennials in the news and by frustrated and tired parents, a meta-analysis by John Protzko says that children are capable of “more self-restraint than previous generations, with their ability to delay gratification having increased by about a minute per decade over the last 50 years” proving themselves to show more self control than prior participants in the ‘Marshmallow Test’ experiment (Protzko, 2017). These findings of increased self-regulation when it comes to gratification are congruent with Mischel’s adolescent follow-up in the original experiment, in which children today have an increase in average IQ, and cognitive abilities (Flynn, 1984).

Though Protzko is reluctant to make a suggestion in terms of correlation, I believe that one can be inferred from the obvious connection of more time studying leading to better grades. Children that can focus less on distractions (such as playing with friends) and more on doing homework usually incur better grades. In a 2004 study by Hefer Bembenutty and Stuart Karabenick, an Academic Delay of Gratification Scale (ADOGS) was created to determine how good a student was at postponing a “immediately available opportunity to satisfy impulses in favor of pursuing academic goals that are more valuable” (Bembenutty and Karabenick, 2004). Those who scored higher on ADOGs had better cognitive strategies such as: organization, rehearsal and elaboration. I think there can also be a connection drawn to the fact that kids now are receiving more homework than ever, sometimes up to three times as much homework than what is recommended (Pressman et al., 2015), thus resulting in longer study times which ultimately make the choice to indulge in gratifying and distracting activities less reasonable.

In conclusion, despite what the general populous thinks about millennials studies have shown that maybe we’re not so bad, and in fact, sometimes we’re better. 😉

Thanks for reading!

References:

Flynn, J. R. (1984). The mean IQ of Americans: Massive gains 1932 to 1978. Psychological bulletin, 95(1), 29.

Bembenutty, H., & Karabenick, S. A. (2004). Inherent association between academic delay of gratification, future time perspective, and self-regulated learning. Educational psychology review, 16(1), 35-57.

Pressman, R. M., Sugarman, D. B., Nemon, M. L., Desjarlais, J., Owens, J. A., & Schettini-Evans, A. (2015). Homework and Family Stress: With Consideration of Parents’ Self Confidence, Educational Level, and Cultural Background. The American Journal of Family Therapy, 43(4), 297-313.

(John Protzko link; i was too lazy to put this into APA format) https://mfr.osf.io/render?url=https://osf.io/jghdm/?action=download%26mode=render