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Why does paraphrasing result in failure to obtain the spacing effect?

Why does paraphrasing result in failure to obtain the spacing effect?



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Dempster, F. N. (1988). The spacing effect: A case study in the failure to apply the results of psychological research. American Psychologist, 43(8), 627 explains that:

One implication of this account is that anything that increases the likelihood that a repetition will receive full processing, such as events that make it difficult to retrieve the results of prior encodings, should improve learning. Thus, this account helps to explain failures to obtain the spacing effect with paraphrased repetitions, that is, repetitions having a changed surface structure (Dellarosa & Bourne, 1985; Glover & Corkill, 1987), and under lengthy lag conditions (Ausubel, 1966; English et al., 1934; Gay, 1973; Lyon, 1914; Peterson et al., 1935; Sones & Stroud, 1940).

I've read this paragraph several times, but cannot understand what it means. The first sentence is very understandable, but I think paraphrasing also increases the likelihood that a repetition will receive full processing and makes it difficult to retrieve the results of prior encodings. If that is the case, then paraphrasing should improve learning. However, the next sentence says:

"this account helps to explain failures to obtain the spacing effect with paraphrased repetitions"(!)

Why?


Short answer
Paraphrasing indeed negates the spacing effect observed in learning, because it causes mass repetition to be as effective as spaced repetition. The confusion is that paraphrasing does not degrade spaced learning, instead it improves the effectiveness of learning through mass repetition up until the level of spaced repetition.

Background
Basically the question is why

The spacing effect fails to occur with paraphrased repetitions

Krug et al. (1990) define the spacing effect as

… [T]he phenomenon in which material encountered on two different occasions with a lapse of time between the encounters is remembered better than material studied for an equal amount of time on one occasion.

Your cited text from Dempster, 1998) reads:

Thus, this account helps to explain failures to obtain the spacing effect with paraphrased repetitions, that is, repetitions having a changed surface structure (Dellarosa & Bourne, 1985; Glover & Corkill, 1987).

Paraphrasing means

[Restating] a text, passage, or work giving the meaning in another form

Now why does this fail to induce the spacing effect? The author cites two papers. The first from Dellarosa & Bourne (1985) states

On the basis of previous research, it was assumed that memory for surface structure of sentences decays rapidly, and hence can contribute to initial identification of repetitions only at short spacings. Because this manipulation should hinder recognition of repetitions as repetitions, it was expected to induce full processing of massed repetitions, and thus facilitate recall of these items.

Why is this important? The authors believe that processing is key to the learning of verbal information. They claim that mass repetition, defined as

[M]aterial studied for an equal amount of time [as spaced repetition] on one occasion

Spaced repetition is believed to be more effective, because the information upon repeated exposures is all fully processed, because it is not recognized by the brain anymore as a full repeat. In contrast, mass repetition leads to incomplete processing during repeated exposures, and hence is not processed fully anymore, because the brain recognizes it as an exact repeat of previously handles material Dellarosa & Bourne (1985). The surface structure of sentences is defined as

[The] representation of a string of words or morphemes as they occur in a sentence, together with labels and brackets that represent syntactic structure.

Changing the surface structure disrupts the brain from recognizing it as an exact repeat. Dellarosa & Bourne (1985) hypothesized that changing the surface structure might prevent the brain from recognizing the same material as exact repeats of information in mass repetition, and thus that learning would become equally effective in mass repetitions. And indeed, their experiments showed that

When sentences were repeated verbatim [] or by the same speaker [], the typical spacing effect was obtained. However, when the surface structure or speaker changed at time of repetition, massed repetitions were recalled nearly as well, or as well as their spaced counterparts.

Subsequently, Glover & Corkill (1987), the second paper Dempster cites, extended these findings to written text, showing the same effect, namely that changing surface structure of texts negated the spacing effect.

Your quote from Dempster, 1998)

The spacing effect fails to occur with paraphrased repetitions

says the same thing, albeit in a condensed and indeed less clear form. It took me quite some detective work to solve this obscure sentence indeed!! Very nice question.

References
- Dempster, American Psychologist (1998); 43(8): 627-34
- Glover & Corkill, J Educational Psychol (1987); 79(2): 198-19
- Krug et al. J Educational Psychol (1990); 82(2): 366-71


Correlation and dependence

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.

Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation).

Formally, random variables are dependent if they do not satisfy a mathematical property of probabilistic independence. In informal parlance, correlation is synonymous with dependence. However, when used in a technical sense, correlation refers to any of several specific types of mathematical operations between the tested variables and their respective expected values. Essentially, correlation is the measure of how two or more variables are related to one another. There are several correlation coefficients, often denoted ρ or r , measuring the degree of correlation. The most common of these is the Pearson correlation coefficient, which is sensitive only to a linear relationship between two variables (which may be present even when one variable is a nonlinear function of the other). Other correlation coefficients – such as Spearman's rank correlation – have been developed to be more robust than Pearson's, that is, more sensitive to nonlinear relationships. [1] [2] [3] Mutual information can also be applied to measure dependence between two variables.


How the Amount and Spacing of Retrieval Practice Affect the Short- and Long-Term Retention of Mathematics Knowledge

Retrieving information from memory increases the likelihood the information will be remembered later. The strategic use of retrieval to enhance memory is known as retrieval practice. Teachers can exert considerable control over students’ retrieval practice, dictating when and how much students practice. Laboratory research has shown that retention benefits from increasing the amount of practice (i.e., the number of times information is retrieved) and from spacing practice out over time. Although retrieval practice is a prominent part of the learning experience in certain educational domains, such as mathematics, relatively little research has examined how retention of actual classroom content is affected by increasing the amount and spacing of retrieval practice. Here, we implemented a complete within-subjects crossing of practice amount (baseline versus increased) and practice spacing (baseline versus increased) in a precalculus course for engineering students. Practice consisted of answering quiz questions. We assessed retention of precalculus knowledge at two educationally relevant time points: the end of the precalculus course (within-semester) and the beginning of a calculus course 4 weeks later (across-semester). Within-semester retention benefited significantly from practicing more and from spacing out practice, although some evidence suggested that the effect of amount of practice was less robust than the effect of spacing. Across-semester retention benefited exclusively from increasing spacing. Given that retaining precalculus knowledge across semesters is crucial for success in higher-level mathematics, these findings support increasing spacing in real-world mathematics education. We discuss how our findings fit within the larger literature on the memory-enhancing effects of retrieval practice.

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To Conclude: Perspectives for Future Research

Psi studies are particularly interesting because whatever the reaction to the question 𠇍oes psi exist?” (Bem and Honorton, 1994), their results affect the whole of psychology. If psi does not exist, significant results for nearly a century have only been obtained by methodological errors, self-deception, fraud, and questionable research practices. How could we avoid such a problem? Since the beginning of the replicability crisis, several solutions have been proposed – pre-registration of study designs, Bayesian statistics, larger N, funnel plots, p-curve analysis, prospective meta-analysis, adversial collaborations, etc., (Bateman et al., 2005) – which could show, at the end, non-significant results in the field of psi studies, revealing that psi was only an illusion. A pre-registration registry has already been set-up in the field of psi research 22 (Watt and Kennedy, 2015, 2017, 2019) as well as statistical guidelines for empirical studies (Tressoldi and Utts, 2015 Kennedy, 2016 Utts and Tressoldi, 2019). Pre-submission to scientific journals which accept a paper on methodological grounds prior to results should also be promoted. In this regard, a “transparent psi project” is currently being conducted which follows these recommendations 23 . Such an approach might be extended to other psi paradigms to confirm or deny the significant results of several meta-analysis (Sherwood and Roe, 2003 Storm et al., 2010 Mossbridge et al., 2012).

On the contrary, if psi does exist, it means that human consciousness can interact with its environment beyond the usual boundaries of space and time, which has fundamental consequences for the way research is conducted in psychology, including psi research (as demonstrated by the psi paradox). As already mentioned, the results of experimental psi research have shown, since their beginning, strange patterns in the data (displacement, reversal, etc.) called notably psi-missing (Rhine, 1952) and elusiveness (Kennedy, 2003). A solution might be to consider these patterns not as an obstacle – or just the effect of randomness (Wiseman, 2010) – but rather as a way to better understand psi and its properties 24 . Following this idea, an original line of research has been initiated by the physicist and psychologist Walter Von Lucadou with the “Model of Pragmatic Information” (MPI Lucadou, 1995 Lucadou et al., 2007). In this model, psi is considered as being something profoundly different to known macro-physical effects and causation, not relying on transfer of information but rather a form of entanglement process depending on the underlying nature of reality (Atmanspacher and Fuchs, 2017 Atmanspacher and Fach, 2019) 25 . A brief metaphor might be useful here. A psi experiment is like an egg where the shell forms an enclosed organizational system. It may be possible to maintain a psi effect as long as the organizational closure is not broken, that is as long as the egg is not broken to see what is inside. In this interpretation, the psi interactions are possible as long as the observer does not interfere with the system (Houtkooper, 2002). Once the system is observed, “the game is over.” This would explain why the source of psi cannot be determined precisely because the determination process would destroy the necessary conditions for the emergence of psi. It also underlines the importance of uncertainty associated with the source of psi. When the latter is used for a transfer of information, the psi effect would be suppressed, especially when attempts are made to replicate exactly the same experimental set. This is what Lucadou calls the “Non-Transmission Axiom” (Lucadou et al., 2007).

Consequently, Lucadou has tried to set-up an experiment in which this type of effect might be maintained by keeping a sufficient level of uncertainty in the system. This experiment uses the 𠇌orrelation Matrix Method” (CMM) in which the global number of correlations between the participants and an experimental task (associated with a RNG) is predicted, but not the location of such correlations in the correlational matrix (Lucadou, 2015 Flores et al., 2018 Walach et al., 2019). The non-transmission axiom could also explain the decline effect and the oscillating trends in the data (Pallikari and Boller, 1997 Maier et al., 2018 Maier and Dechamps, 2018). This last aspect is particularly interesting because these oscillating patterns might be detected, demonstrated, and analyzed when they are compared with classical effects (Rabeyron, 2014).

This line of research appears as an interesting example of what could be conceived as an example of “postmodern psychology” which takes into account the complexity of human consciousness, and more precisely postulates a potential entanglement between the observer and what is observed. It also shows how psi might be implicated in the “hard problem” of consciousness (Chalmers, 2007) or the “problem of measurement” (Wigner, 1963). Even if the possibility that psi exists sounds very implausible to many (Wiseman, 2010 Reber and Alcock, 2020), and as proposed recently by Schooler et al. (2018), a neutral and respectful approach to this topic might open heuristic debates within the wider field of psychology concerning the replicability crisis and the nature of consciousness.


Intellectual Property

The Chicago School of Professional Psychology Intellectual Property Policy    (“IP Policy”) clarifies the rules that govern the ownership rights of intellectual property created by its employees and independent contractors.

It is the policy at The Chicago School that any intellectual property created by a “covered person” within the course and scope of employment or engagement by TCSPP, or during a time period while required or expected to be performing services as an employee or independent contractor of TCSPP, will be owned by TCSPP unless it constitutes Scholarly Work. (A “covered person” consists of all individuals who receive compensation from TCSPP, including student employees, student researchers, employees, and independent contractors.) Generally speaking, TCSPP will also own the research data and results created by a covered person.

“Scholarly work” means scholarly or educational publications, artworks, musical compositions and literary works related to the author’s academic or professional field regardless of the medium of expression (and need not have been created for a specific course), exclusive of any research data or results reflected therein, and includes but is not limited to works authored by students, professionals, faculty and non-faculty researchers.

Each student subject to the IP Policy will be required to sign a written document agreeing to abide by all of the terms of the IP Policy.


5 tips for dealing with non-significant results

It might look like failure, but don&rsquot let go just yet.

When researchers fail to find a statistically significant result, it&rsquos often treated as exactly that &ndash a failure. Non-significant results are difficult to publish in scientific journals and, as a result, researchers often choose not to submit them for publication.

This means that the evidence published in scientific journals is biased towards studies that find effects.

A study published in Science by a team from Stanford University who investigated 221 survey-based experiments funded by the National Science Foundation found that nearly two-thirds of the social science experiments that produced null results were filed away, never to be published.

By comparison, 96% of the studies with statistically strong results were written up.

&ldquoThese biases imperil the robustness of scientific evidence,&rdquo says David Mehler, a psychologist at the University of Münster in Germany. &ldquoBut they also harm early career researchers in particular who depend on building up a track record.&rdquo

Mehler is the co-author of a recent article published in the Journal of European Psychology Students about appreciating the significance of non-significant findings.

So, what can researchers do to avoid unpublishable results?

#1: Perform an equivalence test

The problem with a non-significant result is that it&rsquos ambiguous, explains Daniël Lakens, a psychologist at Eindhoven University of Technology in the Netherlands.

It could mean that the null hypothesis is true &ndash there really is no effect. But it could also indicate that the data are inconclusive either way.

Lakens says performing an &lsquoequivalence test&rsquo can help you distinguish between these two possibilities. It can&rsquot tell you that there is no effect, but it can tell you that an effect &ndash if it exists &ndash is likely to be of negligible practical or theoretical significance.

Bayesian statistics offer an alternative way of performing this test, and in Lakens&rsquo experience, &ldquoeither is better than current practice&rdquo.

#2 Collaborate to collect more data

Equivalence tests and Bayesian analyses can be helpful, but if you don&rsquot have enough data, their results are likely to be inconclusive.

&ldquoThe root problem remains that researchers want to conduct confirmatory hypothesis tests for effects that their studies are mostly underpowered to detect,&rdquo says Mehler.

This, he adds, is a particular problem for students and early career researchers, whose limited resources often constrain them to small sample sizes.

One solution is to collaborate with other researchers to collect more data. In psychology, the StudySwap website is one way for researchers to team up and combine resources.

#3 Use directional tests to increase statistical power

If resources are scarce, it&rsquos important to use them as efficiently as possible. Lakens suggests a number of ways in which researchers can tweak their research design to increase statistical power &ndash the likelihood of finding an effect if it really does exist.

In some circumstances, he says, researchers should consider &lsquodirectional&rsquo or &lsquoone-sided&rsquo tests.

For example, if your hypothesis clearly states that patients receiving a new drug should have better outcomes than those receiving a placebo, it makes sense to test that prediction rather than looking for a difference between the groups in either direction.

&ldquoIt&rsquos basically free statistical power just for making a prediction,&rdquo says Lakens.

#4 Perform sequential analyses to improve data collection efficiency

Efficiency can also be increased by conducting sequential analyses, whereby data collection is terminated if there is already enough evidence to support the hypothesis, or it&rsquos clear that further data will not lead to it being supported.

This approach is often taken in clinical trials where it might be unethical to test patients beyond the point that the efficacy of the treatment can already be determined.

A common concern is that performing multiple analyses increases the probability of finding an effect that doesn&rsquot exist. However, this can be addressed by adjusting the threshold for statistical significance, Lakens explains.

#5 Submit a Registered Report

Whichever approach is taken, it&rsquos important to describe the sampling and analyses clearly to permit a fair evaluation by peer reviewers and readers, says Mehler.

Ideally, studies should be preregistered. This allows authors to demonstrate that the tests were determined before rather than after the results were known. In fact, Mehler argues, the best way to ensure that results are published is to submit a Registered Report.

In this format, studies are evaluated and provisionally accepted based on the methods and analysis plan. The paper is then guaranteed to be published if the researchers follow this preregistered plan &ndash whatever the results.

In a recent investigation, Mehler and his colleague, Chris Allen from Cardiff University in the UK, found that Registered Reports led to a much increased rate of null results: 61% compared with 5 to 20% for traditional papers.


Emphasizing Therapeutic Techniques Over Relationship Building

We rush home from the seminars, and can hardly wait for the first patient that we can try out our newfound knowledge on. Many of these innovations do have credibility, but there is one glitch in all of the focus on techniques. Decades of research have consistently demonstrated that the most powerful predictor of positive therapeutic outcome depends less on what type of therapeutic interventions you employ, and more on what kind of therapist-client bond you develop.

An intern related to her ever-patient supervisor that she had been learning about the use of &ldquoparadoxical intentions&rdquo in her advanced counseling class. She was hoping to try out this new dramatic technique with one of her clients, and did so with a patient during their very first session. The patient had returned to school after a recent divorce, and complained of being totally overwhelmed. She couldn&rsquot get herself to do any homework and was no longer the organized housewife she used to be--failing to do even the simplest of chores like laundry or dishes. The intervention the intern tried was to &ldquo join the symptom&rdquo and prescribe the homework assignment to do &ldquoabsolutely no work at all this week,&rdquo then report back at the next session about how this went.

Unfortunately, there was no next session--the client was never heard from again. The lesson here is one that is all too commonly missed: the therapeutic relationship trumps technique. To be more precise, no other single factor affects therapy outcomes more than the quality of the client-therapist relationship. Although exact percentages of therapeutic effect are difficult to ascertain, one study did attempt to do just that. After reviewing over a hundred outcome studies, Lambert and Barley 1 derived an estimate of the relative contribution of the myriad factors which have been studied in outcome research. Surprisingly, the specific techniques employed by therapists (cognitive, psychodynamic, etc.), accounted for only 30 percent of therapeutic outcome. However, the quality of the client-therapist relationship predicted results 40 percent of the time.

In the case discussed above, the paradoxical intervention might have proven effective in the long run, if the therapist and client had developed enough rapport and a trusting relationship before implementing the approach. The tendency to rush into the therapist tool kit and resolve the problem quickly is of course exacerbated by the current emphasis on brief or time-limited therapy. Suffice it to say, this bottom-line, time-is-money orientation is not always in the patient&rsquos best interests. Relationship building begins with the first hello and handshake. In fact, in one study of medical doctors, the handshake was cited by patients on an exit questionnaire as the most positive factor in the office visit.

One of the best (and least utilized) methods to ensure that the therapist and client are on the same page is to employ a relationship assessment tool such as the Working Alliance Inventory developed by Horvath and Greenberg. This user-friendly tool predicts with a high degree of accuracy whether or not a client is at risk of dropping out of therapy. It also points to the areas of disconnect which can be addressed sympathetically with the client.


Anti-Discrimination, Anti-Harassment, and Title IX Policy

The text below is a summary of The Chicago School of Professional Psychology’s Anti-Discrimination, Anti-Harassment and Title IX Policy (“Policy”).  For the full Policy click here. For additional resources, visit the TCSPP Community Website.

Introduction

The Chicago School of Professional Psychology (TCSPP) acknowledges its ethical and statutory responsibility to afford equal treatment and equal opportunity to all persons and thus complies with all applicable laws and directives regarding nondiscrimination and equality of opportunity.  As required by Title VI, Title IX, Section 504 and all other applicable federal and state laws, TCSPP does not discriminate and prohibits discrimination and harassment against its employees, students, and applicants based on race, ethnicity, color, sex, gender, gender identity, gender expression, genetic information,  religion, creed, age (40 years or older), national origin or ancestry, sexual orientation, physical or mental disability, marital or parental status, pregnancy, military or veteran status, political activities/affiliations or any other impermissible reason in its programs and activities (“Protected Category” or “Protected Categories”).

TCSPP is committed to creating and maintaining a safe learning and working environment that is free from unlawful discrimination, harassment and retaliation.  The Policy prohibits discrimination, harassment, and Sexual Misconduct, which includes Sexual Harassment, and all other forms of discrimination and harassment based on membership in any Protected Category.  The Policy also prohibits retaliation against anyone who exercises their rights under the Policy.

The Policy applies to all employees, students, and other TCSPP Community Members. TCSPP has jurisdiction to investigate conduct occurring on TCSPP’s campuses, in connection with its educational programs, activities, and services, or that puts TCSPP Community Members at risk of serious harm or otherwise creates a hostile learning and/or working environment.

Discrimination

Discrimination is adverse action taken against or harassment of an individual based on membership in any Protected Category. 

Harassment refers to unwelcome behavior based on membership in any Protected Category. Harassment becomes impermissible where 1) enduring the offensive conduct becomes a condition for any academic-related purpose, or 2) the conduct is severe or pervasive enough to create an academic environment that a reasonable prudent person would consider intimidating, hostile, or abusive.

Sexual Harassment, as an umbrella category includes the offenses of sexual harassment, sexual assault, domestic violence, dating violence, and stalking, and is defined as:

Conduct on the basis of sex that satisfies one or more of the following: quid pro quo, sexual harassment, sexual assault, dating violence, domestic violence, stalking as defined in the full Policy.  Sexual Harassment may fall within or outside of the Title IX definition of Sexual Harassment found in Appendix B of the full Policy.

Petty slights, annoyances, and isolated incidents will not rise to the level of violation of a TCSPP policy or rule. To be considered a violation, the conduct must create an environment that would be intimidating, hostile, or offensive to a reasonable person.

Offensive conduct may include but is not limited to jokes, slurs, epithets or name calling, physical assaults or threats, intimidation, ridicule or mockery, insults or put-downs, offensive objects or pictures, or interference with academic performance.

When discriminatory harassment rises to the level of creating a hostile environment, TCSPP may also impose sanctions on the Respondent through the application of the appropriate grievance process set forth in the Policy.

The Policy includes a prohibition of online and cyber manifestations of any of the behaviors prohibited through this policy when those behaviors occur in or have an effect on TCSPP’s education program and activities or use TCSPP networks, technology, or equipment.

Retaliation

TCSPP also bars retaliation against any person who exercises their rights under the Policy, including filing a good faith report of discrimination or harassment, participating in the complaint resolution procedures relating to the same, supporting a Complainant or Respondent, or assisting in providing information relevant to an investigation.

Reporting Complaints of Discrimination, Harassment or Retaliation

A student who believes they have been subject to unlawful discrimination, harassment or retaliation on the basis of a Protected Category, whether by faculty members, employees, training supervisors, visitors or other students, should report such matters to Jennifer Stripe Portillo, Dean for Student Success and Title IX Coordinator. Preparation of a written complaint may be required depending on the basis for the complaint. Complaints should include details of the incident or incidents, names of the individuals involved, names of any witnesses and any documents supporting the complaint.

For the full Policy click here. For additional resources, visit the TCSPP Community Website .

Response to Complaints - Resolution Processes

When a complaint is received, it will be acted on promptly and appropriately. The process used to address the complaint will depend on the subject matter of the complaint.  For complaints of Title IX Sexual Harassment, the Title IX Grievance Process, as described in Section C of the Policy, will be used.  For all other complaints, the General Discrimination, Harassment and Retaliation Resolution Process, as described in Section B of the Policy, will be used.  In some instances, an informal resolution process may be used, if deemed appropriate. Complaints and investigations will be handled on a confidential basis, to the extent possible, with regard for the rights of Complainants and Respondents. Information about the complaint and investigation will only be released on a need-to-know basis, or as otherwise required or permitted by law.

Other Reporting Options

A student may also decide to report to law enforcement, if applicable, although they are not required to do so. Reporting of sexual assault, domestic violence, dating violence, and stalking to the police does not commit the Complainant to further legal action. However, the earlier an incident is reported, the easier it will be for the police to investigate if the Complainant decides to proceed with criminal charges. Early reporting makes it more likely that the police will be able gather needed evidence before it is lost or destroyed, and that the Complainant will receive timely notice of potentially helpful survivor/witness services.

In addition, a student may contact a professional counselor, domestic violence counselor or pastoral counselor, not connected to TCSPP, either through Student Solutions, or through other agencies or resources. Information about Student Solutions and other resources are available on the TCSPP Community Website. TCSPP encourages community members who have experienced sexual misconduct to immediately report the incident to the local police department or another area law enforcement agency. 

Supportive Measures

Complainants and Respondents may request supportive measures, including but not limited to academic support, extensions of academic deadlines, class schedule modifications, withdrawals, leaves of absence, no-contact order, student financial aid counseling and referral to counseling, medical or other healthcare services and visa and immigration assistance, which shall be provided, as deemed appropriate, in accordance with the Policy. Supportive measures are non-disciplinary, non-punitive individualized services offered as appropriate, as reasonably available, and without fee or charge to the parties to restore or preserve access to TCSPP’s Education Program or Activity, including measures designed to protect the safety of all parties or TCSPP’s educational environment, and/or deter harassment, discrimination, and/or retaliation.

TCSPP will maintain the privacy of the supportive measures, provided that privacy does not impair TCSPP’s ability to provide the supportive measures. TCSPP will act to ensure as minimal an academic impact on the parties as possible. TCSPP will implement measures in a way that does not unreasonably burden any party.

Emergency Removal

In certain circumstances, the Dean for Student Success/Title IX Coordinator may determine that an emergency removal is appropriate. If that decision is made, the Respondent will be notified of the decision and be given the option to meet with the Dean/Coordinator prior to such emergency removal being imposed or as soon thereafter as reasonably possible to show cause why the action should not be implemented or should be modified.

Title IX Advisors

The Complainant and Respondent are entitled to have a Title IX Advisor of their choosing accompany them to any meeting or proceeding within the Title IX Formal Grievance process, if they so choose. The parties may select whoever they wish to serve as their Title IX Advisor as long as the Title IX Advisor is eligible and available. At the hearing, cross-examination is required and must be conducted by the parties’ Title IX Advisors. The parties are not permitted to directly cross-examine each other or any witnesses. If a party does not have a Title IX Advisor for a hearing, TCSPP will appoint a trained Title IX Advisor for the limited purpose of conducting any cross-examination during the hearing.  Contact the Title IX Coordinator to obtain a list of those individuals available to serve as a Title IX Advisor.

Sanctions and Remedial Action

If TCSPP determines that the Policy was violated, sanctions may be imposed and effective remedial action will be taken. Individuals who violate the Policy will be subject to disciplinary action, up to and including removal from TCSPP. In addition, appropriate action will be taken to deter any future unlawful discrimination, harassment or retaliation.

For a student, the sanctions that may be imposed include:

  • Formal written warning
  • Professional Development Plan (a plan intended to require reflection and remediation of behavior found to be in violation of this policy)
  • No contact order pertaining to certain TCSPP Community Members or physical locations
  • Referral to counseling and/or Student Solutions
  • Required training or education
  • Dismissal from TCSPP
  • Withholding of degree conferral and/or issuance of a diploma.

The parties have the right to appeal a decision made, in certain circumstances. The details of the appeals process depend on the subject matter of the complaint.  For appeals resulting from a report of Title IX Sexual Harassment, the Appeals process contained within the Title IX Grievance Process, as described in Section C of the Policy, will be used.  For all other appeals, the General Discrimination, Harassment and Retaliation Resolution Process, as described in Section B of the Policy, will be used. 


There are four types of extraneous variables:

There are four types of extraneous variables:

1. Situational Variables

These are aspects of the environment that might affect the participant’s behavior, e.g. noise, temperature, lighting conditions, etc. Situational variables should be controlled so they are the same for all participants.

Standardized procedures are used to ensure that conditions are the same for all participants. This includes the use of standardized instructions

2. Participant / Person Variable

This refers to the ways in which each participant varies from the other, and how this could affect the results e.g. mood, intelligence, anxiety, nerves, concentration etc.

For example, if a participant that has performed a memory test was tired, dyslexic or had poor eyesight, this could effect their performance and the results of the experiment. The experimental design chosen can have an affect on participant variables.

Situational variables also include order effects that can be controlled using counterbalancing, such as giving half the participants condition 'A' first, while the other half get condition 'B' first. This prevents improvement due to practice, or poorer performance due to boredom.

Participant variables can be controlled using random allocation to the conditions of the independent variable.

3. Experimenter / Investigator Effects

The experimenter unconsciously conveys to participants how they should behave - this is called experimenter bias.

The experiment might do this by giving unintentional clues to the participants about what the experiment is about and how they expect them to behave. This affects the participants’ behavior.

The experimenter is often totally unaware of the influence which s/he is exerting and the cues may be very subtle but they may have an influence nevertheless.

Also, the personal attributes (e.g. age, gender, accent, manner etc.) of the experiment can affect the behavior of the participants.

4. Demand Characteristics

Demand characteristics are all the clues in an experiment which convey to the participant the purpose of the research. Demand characteristics can change the results of an experiment if participants change their behavior to conform to expectations.

Participants will be affected by: (i) their surroundings (ii) the researcher’s characteristics (iii) the researcher’s behavior (e.g. non-verbal communication), and (iv) their interpretation of what is going on in the situation.

Experimenters should attempt to minimize these factors by keeping the environment as natural as possible, carefully following standardized procedures. Finally, perhaps different experimenters should be used to see if they obtain similar results.

Suppose we wanted to measure the effects of Alcohol (IV) on driving ability (DV) we would have to try to ensure that extraneous variables did not affect the results. These variables could include:

• Familiarity with the car: Some people may drive better because they have driven this make of car before.

• Familiarity with the test: Some people may do better than others because they know what to expect on the test.

• Used to drinking. The effects of alcohol on some people may be less than on others because they are used to drinking.

• Full stomach. The effect of alcohol on some subjects may be less than on others because they have just had a big meal.

If these extraneous variables are not controlled they may become confounding variables, because they could go on to affect the results of the experiment.


Retrieval-Induced Forgetting and Inhibition

6.2 Novel Tasks

When retrieval practice takes the form of a cued recall test, using a different memory task is another way to alter the retrieval cues. If it is assumed that different retrieval tasks access the same underlying memory representation, inhibition theory predicts that RIF should still be observed. There is extensive evidence for RIF in recognition. Retrieval practice with recall has been shown to decrease recognition accuracy for related items ( Gomez-Ariza et al., 2005 Hicks & Starns, 2004 Racsmány, Conway, Garab, & Nagymate, 2008 Saunders & MacLeod, 2002 Spitzer & Bäuml, 2007, 2009 Spitzer, Hanslmayr, Opitz, Mecklinger, & Bäuml, 2009 Verde, 2004b Verde and Perfect (2011) but see Koutstaal et al., 1999 ), although some studies have observed the effect in response latencies rather than accuracy ( Racsmány et al., 2008 Veling & van Knippenberg, 2004 ). These findings have been put forward as strong evidence for cue independence.

Verde and Perfect (2011) , however, have argued that the case for cue independence based on recognition data is less clear than it might seem. It has often been suggested that recognition may depend on multiple retrieval processes. This view is most commonly associated with dual-process theories, which hold that recognition judgments draw upon the output of two distinct processes, familiarity and recollection ( Yonelinas, 2002 ). Familiarity is a relatively fast process that produces a context-free sense of “oldness.” Recollection is a slower search for specific episodic details and context. Cue independence predicts that retrieval practice should have a negative effect on both familiarity and recollection if an underlying memory representation is rendered inaccessible, retrieval failure will result no matter the route of access. The difficulty is that this prediction cannot be verified by examining recognition performance if the relative contribution of the component processes is unknown (see Verde, 2004a, b ). Decreased accuracy following retrieval practice could be due to a diminished output of familiarity, recollection, or both. Findings from recognition studies provide strong support for cue independence only if it can be verified that both processes suffer from the effects of RIF.

Spitzer and Bäuml (2007) compared the ability of several formal models to accommodate their data showing RIF in recognition. They found that the fits of two formal dual-process models localized the RIF effect to familiarity rather than recollection. This is a surprising result, first because it is predicted by no extant theory, and second because RIF is observed in source recognition ( Hicks & Starns, 2004 Spitzer & Bäuml, 2009 ) and associative recognition ( Verde, 2004b ), memory tasks that rely on recollection. Spitzer and Bäuml also found that neither of the dual-process models fit the data as well as a unidimensional signal-detection model. The latter model is often associated with familiarity-based theories. However, because the model is also open to dual-process interpretation ( Verde & Perfect, 2011 Wixted & Mickes, 2010 ), its ability to accommodate the data says little about whether RIF affects familiarity, recollection, or both.

Other empirical evidence suggests that RIF may be specific to recollection. Verde (2004b) manipulated study duration in an associative recognition task. Because recollection depends on more complex and detailed information than familiarity, limiting encoding time should limit the utility of recollection. A RIF effect was observed following long but not short study durations. Verde and Perfect (2011) manipulated the availability of recollection at retrieval using a response deadline in an item-recognition task. A RIF effect emerged when recognition was self-paced but not when participants were forced to make their judgments very quickly. Both sets of findings suggest that when participants are forced to rely primarily on familiarity, RIF disappears. This is inconsistent with cue independence if it is assumed that recollection and familiarity draw upon the same memory representation. If RIF is indeed specific to recollection, this undermines the usefulness of recognition as support for cue independence in another way. Recollection is similar to recall both theoretically and in its empirical properties ( Verde, 2004a, b ). If people who rely on recollection in recognition are essentially using a form of recall, then the implicit reinstatement of original retrieval cues becomes as much an issue in recognition as it is in recall.

Although changing the retrieval task from recall to recognition has been generally found to preserve RIF, the results have been far less consistent with implicit tasks which do not ask participants to draw on memory for previously encountered materials. Bajo, Gómez-Ariza, Fernandez, and Marful (2006) observed RIF in a word stem completion task using categories consisting of orthographically related words. Butler, Williams, Zacks, and Maki (2001) and Perfect, Moulin, Conway, and Perry (2002) reported no RIF in word fragment and word stem completion using semantic categories. Veling and van Knippenberg (2004) observed RIF in lexical decision, whereas Racsmány and Conway (2006) found that RIF was often absent in lexical decision. Perfect et al. (2002) observed no RIF in a task requiring the generation of category exemplars, although Camp et al. (2005) found it in a subset of participants, and Brown et al. (2005) found that exemplar generation produced output interference. Perfect et al. (2002) observed no RIF in a task requiring the verification of category membership, and no RIF in perceptual identification.

In recall, it has been suggested that RIF may occur with novel cues because people covertly reinstate the original cues used during retrieval practice ( Camp et al., 2005, 2007, 2009 Perfect et al., 2004 ). A similar explanation might be applied to the findings from implicit memory tasks. The use of an implicit task does not rule out the possibility that participants covertly relate the task to prior learning episodes. However, it does make participants less likely to do so, which may be the reason that RIF is much less consistently found in implicit tasks compared to explicit tasks like recall and recognition. Two studies support this explanation by showing that RIF in implicit tasks may rely on conscious reference to the original retrieval cues. Camp et al. (2005) observed RIF in an exemplar generation task but only among participants who reported consciously trying to remember items from an earlier part of the experiment. Racsmány and Conway (2006) found that participants who studied category–exemplar pairs (fruitorange) showed a RIF effect in lexical decisions for the exemplar when primed with the explicitly studied category (fruit) but not with a novel category (food).


Retrieval-Induced Forgetting and Inhibition

6.2 Novel Tasks

When retrieval practice takes the form of a cued recall test, using a different memory task is another way to alter the retrieval cues. If it is assumed that different retrieval tasks access the same underlying memory representation, inhibition theory predicts that RIF should still be observed. There is extensive evidence for RIF in recognition. Retrieval practice with recall has been shown to decrease recognition accuracy for related items ( Gomez-Ariza et al., 2005 Hicks & Starns, 2004 Racsmány, Conway, Garab, & Nagymate, 2008 Saunders & MacLeod, 2002 Spitzer & Bäuml, 2007, 2009 Spitzer, Hanslmayr, Opitz, Mecklinger, & Bäuml, 2009 Verde, 2004b Verde and Perfect (2011) but see Koutstaal et al., 1999 ), although some studies have observed the effect in response latencies rather than accuracy ( Racsmány et al., 2008 Veling & van Knippenberg, 2004 ). These findings have been put forward as strong evidence for cue independence.

Verde and Perfect (2011) , however, have argued that the case for cue independence based on recognition data is less clear than it might seem. It has often been suggested that recognition may depend on multiple retrieval processes. This view is most commonly associated with dual-process theories, which hold that recognition judgments draw upon the output of two distinct processes, familiarity and recollection ( Yonelinas, 2002 ). Familiarity is a relatively fast process that produces a context-free sense of “oldness.” Recollection is a slower search for specific episodic details and context. Cue independence predicts that retrieval practice should have a negative effect on both familiarity and recollection if an underlying memory representation is rendered inaccessible, retrieval failure will result no matter the route of access. The difficulty is that this prediction cannot be verified by examining recognition performance if the relative contribution of the component processes is unknown (see Verde, 2004a, b ). Decreased accuracy following retrieval practice could be due to a diminished output of familiarity, recollection, or both. Findings from recognition studies provide strong support for cue independence only if it can be verified that both processes suffer from the effects of RIF.

Spitzer and Bäuml (2007) compared the ability of several formal models to accommodate their data showing RIF in recognition. They found that the fits of two formal dual-process models localized the RIF effect to familiarity rather than recollection. This is a surprising result, first because it is predicted by no extant theory, and second because RIF is observed in source recognition ( Hicks & Starns, 2004 Spitzer & Bäuml, 2009 ) and associative recognition ( Verde, 2004b ), memory tasks that rely on recollection. Spitzer and Bäuml also found that neither of the dual-process models fit the data as well as a unidimensional signal-detection model. The latter model is often associated with familiarity-based theories. However, because the model is also open to dual-process interpretation ( Verde & Perfect, 2011 Wixted & Mickes, 2010 ), its ability to accommodate the data says little about whether RIF affects familiarity, recollection, or both.

Other empirical evidence suggests that RIF may be specific to recollection. Verde (2004b) manipulated study duration in an associative recognition task. Because recollection depends on more complex and detailed information than familiarity, limiting encoding time should limit the utility of recollection. A RIF effect was observed following long but not short study durations. Verde and Perfect (2011) manipulated the availability of recollection at retrieval using a response deadline in an item-recognition task. A RIF effect emerged when recognition was self-paced but not when participants were forced to make their judgments very quickly. Both sets of findings suggest that when participants are forced to rely primarily on familiarity, RIF disappears. This is inconsistent with cue independence if it is assumed that recollection and familiarity draw upon the same memory representation. If RIF is indeed specific to recollection, this undermines the usefulness of recognition as support for cue independence in another way. Recollection is similar to recall both theoretically and in its empirical properties ( Verde, 2004a, b ). If people who rely on recollection in recognition are essentially using a form of recall, then the implicit reinstatement of original retrieval cues becomes as much an issue in recognition as it is in recall.

Although changing the retrieval task from recall to recognition has been generally found to preserve RIF, the results have been far less consistent with implicit tasks which do not ask participants to draw on memory for previously encountered materials. Bajo, Gómez-Ariza, Fernandez, and Marful (2006) observed RIF in a word stem completion task using categories consisting of orthographically related words. Butler, Williams, Zacks, and Maki (2001) and Perfect, Moulin, Conway, and Perry (2002) reported no RIF in word fragment and word stem completion using semantic categories. Veling and van Knippenberg (2004) observed RIF in lexical decision, whereas Racsmány and Conway (2006) found that RIF was often absent in lexical decision. Perfect et al. (2002) observed no RIF in a task requiring the generation of category exemplars, although Camp et al. (2005) found it in a subset of participants, and Brown et al. (2005) found that exemplar generation produced output interference. Perfect et al. (2002) observed no RIF in a task requiring the verification of category membership, and no RIF in perceptual identification.

In recall, it has been suggested that RIF may occur with novel cues because people covertly reinstate the original cues used during retrieval practice ( Camp et al., 2005, 2007, 2009 Perfect et al., 2004 ). A similar explanation might be applied to the findings from implicit memory tasks. The use of an implicit task does not rule out the possibility that participants covertly relate the task to prior learning episodes. However, it does make participants less likely to do so, which may be the reason that RIF is much less consistently found in implicit tasks compared to explicit tasks like recall and recognition. Two studies support this explanation by showing that RIF in implicit tasks may rely on conscious reference to the original retrieval cues. Camp et al. (2005) observed RIF in an exemplar generation task but only among participants who reported consciously trying to remember items from an earlier part of the experiment. Racsmány and Conway (2006) found that participants who studied category–exemplar pairs (fruitorange) showed a RIF effect in lexical decisions for the exemplar when primed with the explicitly studied category (fruit) but not with a novel category (food).


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McLeod, S. A. (2007) BF Skinner: Operant conditioning. Retrieved September 9, 2009, from The Simply Psychology Website: http://www.simplypsychology.pwp.blueyonder.co.uk/operant-conditioning.html

Miner, John B. (2007). Organizational Behavior: From Theory to Practice. Armonk, NY: M.E. Sharp, Inc. Retrieved from +http://books.google.com/books?id=E_NoJzUp1dcC&pg+

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Operant Conditioning: Schedules of Reinforcement . Dir. Jeffrey Walsh. 2013. Youtube.com.

Pedalino, E., & Gamboa, V. U. (1974). Behavior modification and absenteeism: Intervention in one industrial setting. Journal of Applied Psychology, 59, 694-698. Retrieved from http://carmine.se.edu/cvonbergen/bmod_absenteeism.pdf

Pennsylvania State University World Campus (2013). PSYCH 484 Lesson 3: Reinforcement Theory: What are the Rewards for My Work?. Retrieved from https://courses.worldcampus.psu.edu/fa13/psych484/001/content/lesson03/lesson03_09.html

Positive reinforcement. (n.d.). In Dictionary.com's 21st Century Lexicon . Retrieved September 08, 2009, from Dictionary.com website: http://dictionary.reference.com/browse/positive+reinforcement

Raj, J., Nelson, J., & Rao, K. S. P. (2006). Behavior Modification. A Study on the Effects of Some Reinforces to Improve Performance of Employees in a Retail Industry, 30 (6), 844-866. doi:10.1177/014 5445506273222

Redmond, B.F. (2010). Reinforcement Theory: What are the Rewards for My Work? Work Attitudes and Motivation. The Pennsylvania State University World Campus.

Reinforcement theory. (n.d.). In Encyclopedia of Business, 2 nd ed. Retrieved January 26, 2010, from Reference for Business website: http://www.referenceforbusiness.com/management/Pr-Sa/Reinforcement-Theory.html

Reinforcement theory: Encyclopedia of management. (2006). In Helms, M. M. & Cengage, G. (Ed). eNotes.com. Retrieved January 24, 2010, from http://www.enotes.com/management-encyclopedia/reinforcement-theory

Robbins, S. P., Odendaal, A., & Roodt, G. (2009). Organisational behaviour: Global and southern African perspectives (2nd ed.). Cape Town, Africa: Pearson Education South Africa (Pty) Ltd. Retrieved from http://books.google.com/books?id=9-jcsiS8RSoC

Sharma, R.N., & Sharma, R.K. (2003). Advanced Educational Psychology. New Delhi, India: Atlantic

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Provide references for your information above. Make sure to include the citation above.


How the Amount and Spacing of Retrieval Practice Affect the Short- and Long-Term Retention of Mathematics Knowledge

Retrieving information from memory increases the likelihood the information will be remembered later. The strategic use of retrieval to enhance memory is known as retrieval practice. Teachers can exert considerable control over students’ retrieval practice, dictating when and how much students practice. Laboratory research has shown that retention benefits from increasing the amount of practice (i.e., the number of times information is retrieved) and from spacing practice out over time. Although retrieval practice is a prominent part of the learning experience in certain educational domains, such as mathematics, relatively little research has examined how retention of actual classroom content is affected by increasing the amount and spacing of retrieval practice. Here, we implemented a complete within-subjects crossing of practice amount (baseline versus increased) and practice spacing (baseline versus increased) in a precalculus course for engineering students. Practice consisted of answering quiz questions. We assessed retention of precalculus knowledge at two educationally relevant time points: the end of the precalculus course (within-semester) and the beginning of a calculus course 4 weeks later (across-semester). Within-semester retention benefited significantly from practicing more and from spacing out practice, although some evidence suggested that the effect of amount of practice was less robust than the effect of spacing. Across-semester retention benefited exclusively from increasing spacing. Given that retaining precalculus knowledge across semesters is crucial for success in higher-level mathematics, these findings support increasing spacing in real-world mathematics education. We discuss how our findings fit within the larger literature on the memory-enhancing effects of retrieval practice.

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Anti-Discrimination, Anti-Harassment, and Title IX Policy

The text below is a summary of The Chicago School of Professional Psychology’s Anti-Discrimination, Anti-Harassment and Title IX Policy (“Policy”).  For the full Policy click here. For additional resources, visit the TCSPP Community Website.

Introduction

The Chicago School of Professional Psychology (TCSPP) acknowledges its ethical and statutory responsibility to afford equal treatment and equal opportunity to all persons and thus complies with all applicable laws and directives regarding nondiscrimination and equality of opportunity.  As required by Title VI, Title IX, Section 504 and all other applicable federal and state laws, TCSPP does not discriminate and prohibits discrimination and harassment against its employees, students, and applicants based on race, ethnicity, color, sex, gender, gender identity, gender expression, genetic information,  religion, creed, age (40 years or older), national origin or ancestry, sexual orientation, physical or mental disability, marital or parental status, pregnancy, military or veteran status, political activities/affiliations or any other impermissible reason in its programs and activities (“Protected Category” or “Protected Categories”).

TCSPP is committed to creating and maintaining a safe learning and working environment that is free from unlawful discrimination, harassment and retaliation.  The Policy prohibits discrimination, harassment, and Sexual Misconduct, which includes Sexual Harassment, and all other forms of discrimination and harassment based on membership in any Protected Category.  The Policy also prohibits retaliation against anyone who exercises their rights under the Policy.

The Policy applies to all employees, students, and other TCSPP Community Members. TCSPP has jurisdiction to investigate conduct occurring on TCSPP’s campuses, in connection with its educational programs, activities, and services, or that puts TCSPP Community Members at risk of serious harm or otherwise creates a hostile learning and/or working environment.

Discrimination

Discrimination is adverse action taken against or harassment of an individual based on membership in any Protected Category. 

Harassment refers to unwelcome behavior based on membership in any Protected Category. Harassment becomes impermissible where 1) enduring the offensive conduct becomes a condition for any academic-related purpose, or 2) the conduct is severe or pervasive enough to create an academic environment that a reasonable prudent person would consider intimidating, hostile, or abusive.

Sexual Harassment, as an umbrella category includes the offenses of sexual harassment, sexual assault, domestic violence, dating violence, and stalking, and is defined as:

Conduct on the basis of sex that satisfies one or more of the following: quid pro quo, sexual harassment, sexual assault, dating violence, domestic violence, stalking as defined in the full Policy.  Sexual Harassment may fall within or outside of the Title IX definition of Sexual Harassment found in Appendix B of the full Policy.

Petty slights, annoyances, and isolated incidents will not rise to the level of violation of a TCSPP policy or rule. To be considered a violation, the conduct must create an environment that would be intimidating, hostile, or offensive to a reasonable person.

Offensive conduct may include but is not limited to jokes, slurs, epithets or name calling, physical assaults or threats, intimidation, ridicule or mockery, insults or put-downs, offensive objects or pictures, or interference with academic performance.

When discriminatory harassment rises to the level of creating a hostile environment, TCSPP may also impose sanctions on the Respondent through the application of the appropriate grievance process set forth in the Policy.

The Policy includes a prohibition of online and cyber manifestations of any of the behaviors prohibited through this policy when those behaviors occur in or have an effect on TCSPP’s education program and activities or use TCSPP networks, technology, or equipment.

Retaliation

TCSPP also bars retaliation against any person who exercises their rights under the Policy, including filing a good faith report of discrimination or harassment, participating in the complaint resolution procedures relating to the same, supporting a Complainant or Respondent, or assisting in providing information relevant to an investigation.

Reporting Complaints of Discrimination, Harassment or Retaliation

A student who believes they have been subject to unlawful discrimination, harassment or retaliation on the basis of a Protected Category, whether by faculty members, employees, training supervisors, visitors or other students, should report such matters to Jennifer Stripe Portillo, Dean for Student Success and Title IX Coordinator. Preparation of a written complaint may be required depending on the basis for the complaint. Complaints should include details of the incident or incidents, names of the individuals involved, names of any witnesses and any documents supporting the complaint.

For the full Policy click here. For additional resources, visit the TCSPP Community Website .

Response to Complaints - Resolution Processes

When a complaint is received, it will be acted on promptly and appropriately. The process used to address the complaint will depend on the subject matter of the complaint.  For complaints of Title IX Sexual Harassment, the Title IX Grievance Process, as described in Section C of the Policy, will be used.  For all other complaints, the General Discrimination, Harassment and Retaliation Resolution Process, as described in Section B of the Policy, will be used.  In some instances, an informal resolution process may be used, if deemed appropriate. Complaints and investigations will be handled on a confidential basis, to the extent possible, with regard for the rights of Complainants and Respondents. Information about the complaint and investigation will only be released on a need-to-know basis, or as otherwise required or permitted by law.

Other Reporting Options

A student may also decide to report to law enforcement, if applicable, although they are not required to do so. Reporting of sexual assault, domestic violence, dating violence, and stalking to the police does not commit the Complainant to further legal action. However, the earlier an incident is reported, the easier it will be for the police to investigate if the Complainant decides to proceed with criminal charges. Early reporting makes it more likely that the police will be able gather needed evidence before it is lost or destroyed, and that the Complainant will receive timely notice of potentially helpful survivor/witness services.

In addition, a student may contact a professional counselor, domestic violence counselor or pastoral counselor, not connected to TCSPP, either through Student Solutions, or through other agencies or resources. Information about Student Solutions and other resources are available on the TCSPP Community Website. TCSPP encourages community members who have experienced sexual misconduct to immediately report the incident to the local police department or another area law enforcement agency. 

Supportive Measures

Complainants and Respondents may request supportive measures, including but not limited to academic support, extensions of academic deadlines, class schedule modifications, withdrawals, leaves of absence, no-contact order, student financial aid counseling and referral to counseling, medical or other healthcare services and visa and immigration assistance, which shall be provided, as deemed appropriate, in accordance with the Policy. Supportive measures are non-disciplinary, non-punitive individualized services offered as appropriate, as reasonably available, and without fee or charge to the parties to restore or preserve access to TCSPP’s Education Program or Activity, including measures designed to protect the safety of all parties or TCSPP’s educational environment, and/or deter harassment, discrimination, and/or retaliation.

TCSPP will maintain the privacy of the supportive measures, provided that privacy does not impair TCSPP’s ability to provide the supportive measures. TCSPP will act to ensure as minimal an academic impact on the parties as possible. TCSPP will implement measures in a way that does not unreasonably burden any party.

Emergency Removal

In certain circumstances, the Dean for Student Success/Title IX Coordinator may determine that an emergency removal is appropriate. If that decision is made, the Respondent will be notified of the decision and be given the option to meet with the Dean/Coordinator prior to such emergency removal being imposed or as soon thereafter as reasonably possible to show cause why the action should not be implemented or should be modified.

Title IX Advisors

The Complainant and Respondent are entitled to have a Title IX Advisor of their choosing accompany them to any meeting or proceeding within the Title IX Formal Grievance process, if they so choose. The parties may select whoever they wish to serve as their Title IX Advisor as long as the Title IX Advisor is eligible and available. At the hearing, cross-examination is required and must be conducted by the parties’ Title IX Advisors. The parties are not permitted to directly cross-examine each other or any witnesses. If a party does not have a Title IX Advisor for a hearing, TCSPP will appoint a trained Title IX Advisor for the limited purpose of conducting any cross-examination during the hearing.  Contact the Title IX Coordinator to obtain a list of those individuals available to serve as a Title IX Advisor.

Sanctions and Remedial Action

If TCSPP determines that the Policy was violated, sanctions may be imposed and effective remedial action will be taken. Individuals who violate the Policy will be subject to disciplinary action, up to and including removal from TCSPP. In addition, appropriate action will be taken to deter any future unlawful discrimination, harassment or retaliation.

For a student, the sanctions that may be imposed include:

  • Formal written warning
  • Professional Development Plan (a plan intended to require reflection and remediation of behavior found to be in violation of this policy)
  • No contact order pertaining to certain TCSPP Community Members or physical locations
  • Referral to counseling and/or Student Solutions
  • Required training or education
  • Dismissal from TCSPP
  • Withholding of degree conferral and/or issuance of a diploma.

The parties have the right to appeal a decision made, in certain circumstances. The details of the appeals process depend on the subject matter of the complaint.  For appeals resulting from a report of Title IX Sexual Harassment, the Appeals process contained within the Title IX Grievance Process, as described in Section C of the Policy, will be used.  For all other appeals, the General Discrimination, Harassment and Retaliation Resolution Process, as described in Section B of the Policy, will be used. 


Emphasizing Therapeutic Techniques Over Relationship Building

We rush home from the seminars, and can hardly wait for the first patient that we can try out our newfound knowledge on. Many of these innovations do have credibility, but there is one glitch in all of the focus on techniques. Decades of research have consistently demonstrated that the most powerful predictor of positive therapeutic outcome depends less on what type of therapeutic interventions you employ, and more on what kind of therapist-client bond you develop.

An intern related to her ever-patient supervisor that she had been learning about the use of &ldquoparadoxical intentions&rdquo in her advanced counseling class. She was hoping to try out this new dramatic technique with one of her clients, and did so with a patient during their very first session. The patient had returned to school after a recent divorce, and complained of being totally overwhelmed. She couldn&rsquot get herself to do any homework and was no longer the organized housewife she used to be--failing to do even the simplest of chores like laundry or dishes. The intervention the intern tried was to &ldquo join the symptom&rdquo and prescribe the homework assignment to do &ldquoabsolutely no work at all this week,&rdquo then report back at the next session about how this went.

Unfortunately, there was no next session--the client was never heard from again. The lesson here is one that is all too commonly missed: the therapeutic relationship trumps technique. To be more precise, no other single factor affects therapy outcomes more than the quality of the client-therapist relationship. Although exact percentages of therapeutic effect are difficult to ascertain, one study did attempt to do just that. After reviewing over a hundred outcome studies, Lambert and Barley 1 derived an estimate of the relative contribution of the myriad factors which have been studied in outcome research. Surprisingly, the specific techniques employed by therapists (cognitive, psychodynamic, etc.), accounted for only 30 percent of therapeutic outcome. However, the quality of the client-therapist relationship predicted results 40 percent of the time.

In the case discussed above, the paradoxical intervention might have proven effective in the long run, if the therapist and client had developed enough rapport and a trusting relationship before implementing the approach. The tendency to rush into the therapist tool kit and resolve the problem quickly is of course exacerbated by the current emphasis on brief or time-limited therapy. Suffice it to say, this bottom-line, time-is-money orientation is not always in the patient&rsquos best interests. Relationship building begins with the first hello and handshake. In fact, in one study of medical doctors, the handshake was cited by patients on an exit questionnaire as the most positive factor in the office visit.

One of the best (and least utilized) methods to ensure that the therapist and client are on the same page is to employ a relationship assessment tool such as the Working Alliance Inventory developed by Horvath and Greenberg. This user-friendly tool predicts with a high degree of accuracy whether or not a client is at risk of dropping out of therapy. It also points to the areas of disconnect which can be addressed sympathetically with the client.


Intellectual Property

The Chicago School of Professional Psychology Intellectual Property Policy    (“IP Policy”) clarifies the rules that govern the ownership rights of intellectual property created by its employees and independent contractors.

It is the policy at The Chicago School that any intellectual property created by a “covered person” within the course and scope of employment or engagement by TCSPP, or during a time period while required or expected to be performing services as an employee or independent contractor of TCSPP, will be owned by TCSPP unless it constitutes Scholarly Work. (A “covered person” consists of all individuals who receive compensation from TCSPP, including student employees, student researchers, employees, and independent contractors.) Generally speaking, TCSPP will also own the research data and results created by a covered person.

“Scholarly work” means scholarly or educational publications, artworks, musical compositions and literary works related to the author’s academic or professional field regardless of the medium of expression (and need not have been created for a specific course), exclusive of any research data or results reflected therein, and includes but is not limited to works authored by students, professionals, faculty and non-faculty researchers.

Each student subject to the IP Policy will be required to sign a written document agreeing to abide by all of the terms of the IP Policy.


There are four types of extraneous variables:

There are four types of extraneous variables:

1. Situational Variables

These are aspects of the environment that might affect the participant’s behavior, e.g. noise, temperature, lighting conditions, etc. Situational variables should be controlled so they are the same for all participants.

Standardized procedures are used to ensure that conditions are the same for all participants. This includes the use of standardized instructions

2. Participant / Person Variable

This refers to the ways in which each participant varies from the other, and how this could affect the results e.g. mood, intelligence, anxiety, nerves, concentration etc.

For example, if a participant that has performed a memory test was tired, dyslexic or had poor eyesight, this could effect their performance and the results of the experiment. The experimental design chosen can have an affect on participant variables.

Situational variables also include order effects that can be controlled using counterbalancing, such as giving half the participants condition 'A' first, while the other half get condition 'B' first. This prevents improvement due to practice, or poorer performance due to boredom.

Participant variables can be controlled using random allocation to the conditions of the independent variable.

3. Experimenter / Investigator Effects

The experimenter unconsciously conveys to participants how they should behave - this is called experimenter bias.

The experiment might do this by giving unintentional clues to the participants about what the experiment is about and how they expect them to behave. This affects the participants’ behavior.

The experimenter is often totally unaware of the influence which s/he is exerting and the cues may be very subtle but they may have an influence nevertheless.

Also, the personal attributes (e.g. age, gender, accent, manner etc.) of the experiment can affect the behavior of the participants.

4. Demand Characteristics

Demand characteristics are all the clues in an experiment which convey to the participant the purpose of the research. Demand characteristics can change the results of an experiment if participants change their behavior to conform to expectations.

Participants will be affected by: (i) their surroundings (ii) the researcher’s characteristics (iii) the researcher’s behavior (e.g. non-verbal communication), and (iv) their interpretation of what is going on in the situation.

Experimenters should attempt to minimize these factors by keeping the environment as natural as possible, carefully following standardized procedures. Finally, perhaps different experimenters should be used to see if they obtain similar results.

Suppose we wanted to measure the effects of Alcohol (IV) on driving ability (DV) we would have to try to ensure that extraneous variables did not affect the results. These variables could include:

• Familiarity with the car: Some people may drive better because they have driven this make of car before.

• Familiarity with the test: Some people may do better than others because they know what to expect on the test.

• Used to drinking. The effects of alcohol on some people may be less than on others because they are used to drinking.

• Full stomach. The effect of alcohol on some subjects may be less than on others because they have just had a big meal.

If these extraneous variables are not controlled they may become confounding variables, because they could go on to affect the results of the experiment.


To Conclude: Perspectives for Future Research

Psi studies are particularly interesting because whatever the reaction to the question 𠇍oes psi exist?” (Bem and Honorton, 1994), their results affect the whole of psychology. If psi does not exist, significant results for nearly a century have only been obtained by methodological errors, self-deception, fraud, and questionable research practices. How could we avoid such a problem? Since the beginning of the replicability crisis, several solutions have been proposed – pre-registration of study designs, Bayesian statistics, larger N, funnel plots, p-curve analysis, prospective meta-analysis, adversial collaborations, etc., (Bateman et al., 2005) – which could show, at the end, non-significant results in the field of psi studies, revealing that psi was only an illusion. A pre-registration registry has already been set-up in the field of psi research 22 (Watt and Kennedy, 2015, 2017, 2019) as well as statistical guidelines for empirical studies (Tressoldi and Utts, 2015 Kennedy, 2016 Utts and Tressoldi, 2019). Pre-submission to scientific journals which accept a paper on methodological grounds prior to results should also be promoted. In this regard, a “transparent psi project” is currently being conducted which follows these recommendations 23 . Such an approach might be extended to other psi paradigms to confirm or deny the significant results of several meta-analysis (Sherwood and Roe, 2003 Storm et al., 2010 Mossbridge et al., 2012).

On the contrary, if psi does exist, it means that human consciousness can interact with its environment beyond the usual boundaries of space and time, which has fundamental consequences for the way research is conducted in psychology, including psi research (as demonstrated by the psi paradox). As already mentioned, the results of experimental psi research have shown, since their beginning, strange patterns in the data (displacement, reversal, etc.) called notably psi-missing (Rhine, 1952) and elusiveness (Kennedy, 2003). A solution might be to consider these patterns not as an obstacle – or just the effect of randomness (Wiseman, 2010) – but rather as a way to better understand psi and its properties 24 . Following this idea, an original line of research has been initiated by the physicist and psychologist Walter Von Lucadou with the “Model of Pragmatic Information” (MPI Lucadou, 1995 Lucadou et al., 2007). In this model, psi is considered as being something profoundly different to known macro-physical effects and causation, not relying on transfer of information but rather a form of entanglement process depending on the underlying nature of reality (Atmanspacher and Fuchs, 2017 Atmanspacher and Fach, 2019) 25 . A brief metaphor might be useful here. A psi experiment is like an egg where the shell forms an enclosed organizational system. It may be possible to maintain a psi effect as long as the organizational closure is not broken, that is as long as the egg is not broken to see what is inside. In this interpretation, the psi interactions are possible as long as the observer does not interfere with the system (Houtkooper, 2002). Once the system is observed, “the game is over.” This would explain why the source of psi cannot be determined precisely because the determination process would destroy the necessary conditions for the emergence of psi. It also underlines the importance of uncertainty associated with the source of psi. When the latter is used for a transfer of information, the psi effect would be suppressed, especially when attempts are made to replicate exactly the same experimental set. This is what Lucadou calls the “Non-Transmission Axiom” (Lucadou et al., 2007).

Consequently, Lucadou has tried to set-up an experiment in which this type of effect might be maintained by keeping a sufficient level of uncertainty in the system. This experiment uses the 𠇌orrelation Matrix Method” (CMM) in which the global number of correlations between the participants and an experimental task (associated with a RNG) is predicted, but not the location of such correlations in the correlational matrix (Lucadou, 2015 Flores et al., 2018 Walach et al., 2019). The non-transmission axiom could also explain the decline effect and the oscillating trends in the data (Pallikari and Boller, 1997 Maier et al., 2018 Maier and Dechamps, 2018). This last aspect is particularly interesting because these oscillating patterns might be detected, demonstrated, and analyzed when they are compared with classical effects (Rabeyron, 2014).

This line of research appears as an interesting example of what could be conceived as an example of “postmodern psychology” which takes into account the complexity of human consciousness, and more precisely postulates a potential entanglement between the observer and what is observed. It also shows how psi might be implicated in the “hard problem” of consciousness (Chalmers, 2007) or the “problem of measurement” (Wigner, 1963). Even if the possibility that psi exists sounds very implausible to many (Wiseman, 2010 Reber and Alcock, 2020), and as proposed recently by Schooler et al. (2018), a neutral and respectful approach to this topic might open heuristic debates within the wider field of psychology concerning the replicability crisis and the nature of consciousness.


Correlation and dependence

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.

Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation).

Formally, random variables are dependent if they do not satisfy a mathematical property of probabilistic independence. In informal parlance, correlation is synonymous with dependence. However, when used in a technical sense, correlation refers to any of several specific types of mathematical operations between the tested variables and their respective expected values. Essentially, correlation is the measure of how two or more variables are related to one another. There are several correlation coefficients, often denoted ρ or r , measuring the degree of correlation. The most common of these is the Pearson correlation coefficient, which is sensitive only to a linear relationship between two variables (which may be present even when one variable is a nonlinear function of the other). Other correlation coefficients – such as Spearman's rank correlation – have been developed to be more robust than Pearson's, that is, more sensitive to nonlinear relationships. [1] [2] [3] Mutual information can also be applied to measure dependence between two variables.


5 tips for dealing with non-significant results

It might look like failure, but don&rsquot let go just yet.

When researchers fail to find a statistically significant result, it&rsquos often treated as exactly that &ndash a failure. Non-significant results are difficult to publish in scientific journals and, as a result, researchers often choose not to submit them for publication.

This means that the evidence published in scientific journals is biased towards studies that find effects.

A study published in Science by a team from Stanford University who investigated 221 survey-based experiments funded by the National Science Foundation found that nearly two-thirds of the social science experiments that produced null results were filed away, never to be published.

By comparison, 96% of the studies with statistically strong results were written up.

&ldquoThese biases imperil the robustness of scientific evidence,&rdquo says David Mehler, a psychologist at the University of Münster in Germany. &ldquoBut they also harm early career researchers in particular who depend on building up a track record.&rdquo

Mehler is the co-author of a recent article published in the Journal of European Psychology Students about appreciating the significance of non-significant findings.

So, what can researchers do to avoid unpublishable results?

#1: Perform an equivalence test

The problem with a non-significant result is that it&rsquos ambiguous, explains Daniël Lakens, a psychologist at Eindhoven University of Technology in the Netherlands.

It could mean that the null hypothesis is true &ndash there really is no effect. But it could also indicate that the data are inconclusive either way.

Lakens says performing an &lsquoequivalence test&rsquo can help you distinguish between these two possibilities. It can&rsquot tell you that there is no effect, but it can tell you that an effect &ndash if it exists &ndash is likely to be of negligible practical or theoretical significance.

Bayesian statistics offer an alternative way of performing this test, and in Lakens&rsquo experience, &ldquoeither is better than current practice&rdquo.

#2 Collaborate to collect more data

Equivalence tests and Bayesian analyses can be helpful, but if you don&rsquot have enough data, their results are likely to be inconclusive.

&ldquoThe root problem remains that researchers want to conduct confirmatory hypothesis tests for effects that their studies are mostly underpowered to detect,&rdquo says Mehler.

This, he adds, is a particular problem for students and early career researchers, whose limited resources often constrain them to small sample sizes.

One solution is to collaborate with other researchers to collect more data. In psychology, the StudySwap website is one way for researchers to team up and combine resources.

#3 Use directional tests to increase statistical power

If resources are scarce, it&rsquos important to use them as efficiently as possible. Lakens suggests a number of ways in which researchers can tweak their research design to increase statistical power &ndash the likelihood of finding an effect if it really does exist.

In some circumstances, he says, researchers should consider &lsquodirectional&rsquo or &lsquoone-sided&rsquo tests.

For example, if your hypothesis clearly states that patients receiving a new drug should have better outcomes than those receiving a placebo, it makes sense to test that prediction rather than looking for a difference between the groups in either direction.

&ldquoIt&rsquos basically free statistical power just for making a prediction,&rdquo says Lakens.

#4 Perform sequential analyses to improve data collection efficiency

Efficiency can also be increased by conducting sequential analyses, whereby data collection is terminated if there is already enough evidence to support the hypothesis, or it&rsquos clear that further data will not lead to it being supported.

This approach is often taken in clinical trials where it might be unethical to test patients beyond the point that the efficacy of the treatment can already be determined.

A common concern is that performing multiple analyses increases the probability of finding an effect that doesn&rsquot exist. However, this can be addressed by adjusting the threshold for statistical significance, Lakens explains.

#5 Submit a Registered Report

Whichever approach is taken, it&rsquos important to describe the sampling and analyses clearly to permit a fair evaluation by peer reviewers and readers, says Mehler.

Ideally, studies should be preregistered. This allows authors to demonstrate that the tests were determined before rather than after the results were known. In fact, Mehler argues, the best way to ensure that results are published is to submit a Registered Report.

In this format, studies are evaluated and provisionally accepted based on the methods and analysis plan. The paper is then guaranteed to be published if the researchers follow this preregistered plan &ndash whatever the results.

In a recent investigation, Mehler and his colleague, Chris Allen from Cardiff University in the UK, found that Registered Reports led to a much increased rate of null results: 61% compared with 5 to 20% for traditional papers.